Triple
T37673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One World Trade Center |
E745
|
entity |
| Predicate | structuralEngineer |
P616
|
FINISHED |
| Object |
WSP Cantor Seinuk
WSP Cantor Seinuk is a prominent structural engineering firm known for designing high-rise and complex buildings worldwide.
|
E5242
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: WSP Cantor Seinuk | Statement: [One World Trade Center, structuralEngineer, WSP Cantor Seinuk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WSP Cantor Seinuk Context triple: [One World Trade Center, structuralEngineer, WSP Cantor Seinuk]
-
A.
Sullivan & Worcester
Sullivan & Worcester is a Boston-based law firm known for its corporate, tax, and real estate practices and its work with business and financial clients.
-
B.
Skidmore, Owings & Merrill
Skidmore, Owings & Merrill is a prominent American architecture and engineering firm renowned for designing major modernist and high-rise buildings worldwide.
-
C.
Jan Szczepański
Jan Szczepański was a Polish mountaineer known for participating in pioneering high-altitude ascents in the Andes.
-
D.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
E.
Rogers
Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: WSP Cantor Seinuk Triple: [One World Trade Center, structuralEngineer, WSP Cantor Seinuk]
Generated description
WSP Cantor Seinuk is a prominent structural engineering firm known for designing high-rise and complex buildings worldwide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WSP Cantor Seinuk Target entity description: WSP Cantor Seinuk is a prominent structural engineering firm known for designing high-rise and complex buildings worldwide.
-
A.
Sullivan & Worcester
Sullivan & Worcester is a Boston-based law firm known for its corporate, tax, and real estate practices and its work with business and financial clients.
-
B.
Skidmore, Owings & Merrill
Skidmore, Owings & Merrill is a prominent American architecture and engineering firm renowned for designing major modernist and high-rise buildings worldwide.
-
C.
Jan Szczepański
Jan Szczepański was a Polish mountaineer known for participating in pioneering high-altitude ascents in the Andes.
-
D.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
E.
Rogers
Rogers is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24acbb90881908c9f77e74034eb52 |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a255322d048190b3a45c6c6a80230c |
completed | Feb. 28, 2026, 2:38 a.m. |
| NEDg | Description generation | batch_69a255ee9c1c8190a9d1db89af34fbaf |
completed | Feb. 28, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a256a35c3081908aa5522c734bd54d |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.