Triple
T12816593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrow-on-the-Hill railway station |
E306417
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
HOH
HOH is the National Rail station code for Harrow-on-the-Hill railway station in northwest London.
|
E1004255
|
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: HOH | Statement: [Harrow-on-the-Hill railway station, hasStationCode, HOH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HOH Context triple: [Harrow-on-the-Hill railway station, hasStationCode, HOH]
-
A.
HOL
HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
-
B.
HO
HO is the stock ticker symbol for Thales Group, a major French multinational company specializing in aerospace, defense, security, and transportation technologies.
-
C.
HO
HO is the vehicle registration code used on license plates for the city and district of Hof in Upper Franconia, Germany.
-
D.
HO
HO is the IATA airline designator assigned to Juneyao Air, a Chinese carrier based in Shanghai.
-
E.
Ho
Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
- 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: HOH Triple: [Harrow-on-the-Hill railway station, hasStationCode, HOH]
Generated description
HOH is the National Rail station code for Harrow-on-the-Hill railway station in northwest London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HOH Target entity description: HOH is the National Rail station code for Harrow-on-the-Hill railway station in northwest London.
-
A.
HOL
HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
-
B.
HO
HO is the stock ticker symbol for Thales Group, a major French multinational company specializing in aerospace, defense, security, and transportation technologies.
-
C.
HO
HO is the vehicle registration code used on license plates for the city and district of Hof in Upper Franconia, Germany.
-
D.
HO
HO is the IATA airline designator assigned to Juneyao Air, a Chinese carrier based in Shanghai.
-
E.
Ho
Ho is the given name of the Korean-born contemporary artist Do Ho Suh, known for his large-scale installations exploring space, memory, and identity.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9d00088190ac0f5d60e1de7a7c |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ecee33c8190a6bf045731bb9326 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f691341d0081909ca3b281ee64b42b |
completed | May 3, 2026, 12:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f692361c3c81909078a19be1a86231 |
completed | May 3, 2026, 12:09 a.m. |
Created at: April 9, 2026, 5:31 p.m.