Triple
T114544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masonic lodge |
E2315
|
entity |
| Predicate | hasOfficer |
P537
|
FINISHED |
| Object |
Tyler
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
|
E30784
|
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: Tyler | Statement: [Masonic lodge, hasOfficer, Tyler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tyler Context triple: [Masonic lodge, hasOfficer, Tyler]
-
A.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
B.
Jamie
Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
-
C.
Gavin
Gavin is a masculine given name of Celtic origin, commonly used in English-speaking countries.
-
D.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
E.
Sean Taylor
Sean Taylor was a hard-hitting Pro Bowl safety for the Washington NFL franchise whose promising career was tragically cut short by his death in 2007.
- 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: Tyler Triple: [Masonic lodge, hasOfficer, Tyler]
Generated description
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tyler Target entity description: Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
-
A.
Neal
Neal is a masculine given name of Gaelic origin, commonly used in English-speaking countries.
-
B.
Jamie
Jamie is a given name commonly used as a diminutive or variant of James, and is borne by people of all genders in English-speaking countries.
-
C.
Gavin
Gavin is a masculine given name of Celtic origin, commonly used in English-speaking countries.
-
D.
Lee
Lee is a given name shared by numerous individuals across different cultures and professions.
-
E.
Sean Taylor
Sean Taylor was a hard-hitting Pro Bowl safety for the Washington NFL franchise whose promising career was tragically cut short by his death in 2007.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a256effaac81908c22be65d9f668a4 |
completed | Feb. 28, 2026, 2:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3672af4fc8190a99265c93181be5d |
completed | Feb. 28, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69a367aa62f481908414358a21667187 |
completed | Feb. 28, 2026, 10:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3686970ac81908ba7efe90feb26fd |
completed | Feb. 28, 2026, 10:12 p.m. |
Created at: Feb. 28, 2026, 2:24 a.m.