Triple
T13493350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbott, Texas |
E320693
|
entity |
| Predicate | namedFor |
P63
|
FINISHED |
| Object | Joseph Abbott |
E256721
|
NE FINISHED |
How this triple was built (2 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: Joseph Abbott | Statement: [Abbott, Texas, namedFor, Joseph Abbott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joseph Abbott Context triple: [Abbott, Texas, namedFor, Joseph Abbott]
-
A.
Joseph Abbott
chosen
Joseph Abbott was a notable figure in Texas history, likely a politician or community leader, after whom the town of Abbott, Texas, was named.
-
B.
Fred Abbott
Fred Abbott is a musician best known as a member of the English indie folk band Noah and the Whale.
-
C.
Philip Abbott
Philip Abbott was an American character actor best known for his extensive work in film and television from the 1950s through the 1980s.
-
D.
William Louis Abbott
William Louis Abbott was an American physician, explorer, and naturalist known for his extensive zoological and ethnographic collections in Asia and the Indian Ocean region.
-
E.
John Abernethy
John Abernethy was a prominent 18th–19th century English surgeon and anatomist known for his influential teaching and writings that helped shape modern surgical practice.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4c66008190b287e0551889d7c8 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7463d3a948190aab07a25fd903d4e |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:43 p.m.