Triple
T1009462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gassel |
E21788
|
entity |
| Predicate | mergedInto |
P77
|
FINISHED |
| Object | Beers |
E113277
|
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: Beers | Statement: [Gassel, mergedInto, Beers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beers Context triple: [Gassel, mergedInto, Beers]
-
A.
Beers
chosen
Beers is a small village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Land van Cuijk.
-
B.
Beery
Beery is a surname most notably associated with the American acting family that includes character actor Noah Beery and his relatives.
-
C.
Beer-lahai-roi
Beer-lahai-roi is a biblical location in the Negev desert region, known as the well where Hagar encountered God and later associated with the life of the patriarch Isaac.
-
D.
Mead
Mead is a common English surname borne by various notable individuals, including the influential cultural anthropologist Margaret Mead.
-
E.
Beer Kill
Beer Kill is a small stream in New York’s Hudson Valley that serves as a tributary within the Rondout Creek watershed.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a3cb608190a2de34a09cd55146 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3ba9406c81909a13375fea05ee99 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.