Triple
T8862408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bucholz Army Airfield |
E210923
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Bucholz
Bucholz is the namesake of Bucholz Army Airfield, likely a military figure commemorated for service or significance to the U.S. armed forces.
|
E762225
|
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: Bucholz | Statement: [Bucholz Army Airfield, namedAfter, Bucholz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bucholz Context triple: [Bucholz Army Airfield, namedAfter, Bucholz]
-
A.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
B.
Daboll
Daboll is a surname most prominently associated with Brian Daboll, a professional American football coach in the National Football League.
-
C.
Zaslofsky
Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
-
D.
Altobelli
Altobelli is an Italian surname most notably associated with figures in professional baseball and football, including former MLB manager Joe Altobelli.
-
E.
Keefer
Keefer was a distinguished racing greyhound renowned for its achievements on the track, earning induction into the Greyhound Hall of Fame.
- 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: Bucholz Triple: [Bucholz Army Airfield, namedAfter, Bucholz]
Generated description
Bucholz is the namesake of Bucholz Army Airfield, likely a military figure commemorated for service or significance to the U.S. armed forces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bucholz Target entity description: Bucholz is the namesake of Bucholz Army Airfield, likely a military figure commemorated for service or significance to the U.S. armed forces.
-
A.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
B.
Daboll
Daboll is a surname most prominently associated with Brian Daboll, a professional American football coach in the National Football League.
-
C.
Zaslofsky
Zaslofsky is a surname most notably associated with Max Zaslofsky, an early star guard in the National Basketball Association.
-
D.
Altobelli
Altobelli is an Italian surname most notably associated with figures in professional baseball and football, including former MLB manager Joe Altobelli.
-
E.
Keefer
Keefer was a distinguished racing greyhound renowned for its achievements on the track, earning induction into the Greyhound Hall of Fame.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc610263048190931bb2c3ac573a08 |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0c248108190815d593f44029183 |
completed | April 3, 2026, 11:13 a.m. |
| NEDg | Description generation | batch_69cfa1714b4081909035c9b15c82c1be |
completed | April 3, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa24be80481909e2b575f99cd1dc4 |
completed | April 3, 2026, 11:19 a.m. |
Created at: March 30, 2026, 6:50 p.m.