Triple
T9199946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Gilroy |
E220811
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gilroy |
E622691
|
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: Gilroy | Statement: [Dan Gilroy, familyName, Gilroy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilroy Context triple: [Dan Gilroy, familyName, Gilroy]
-
A.
Gilroy
chosen
Gilroy is a Scottish surname and sept historically associated with Clan Grant in the Scottish Highlands.
-
B.
Gilroy
Gilroy is a city in Santa Clara County, California, known for its garlic production and as the southern endpoint of Caltrain commuter rail service.
-
C.
San Luis Obispo
San Luis Obispo is a small coastal city in California known for its historic downtown, nearby beaches and wineries, and its location along the scenic Highway 1 between Los Angeles and San Francisco.
-
D.
Santa Rosa
Santa Rosa is the principal city and administrative center of Argentina’s La Pampa Province, known for its role as a regional hub in the country’s central plains.
-
E.
Santa Rosa
Santa Rosa is a residential barrio (neighborhood) within the municipality of Dorado, Puerto Rico.
- 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_69ca83e8e9248190862cf3e41693b310 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd881c5d48190bbc33fac71a1d849 |
completed | April 1, 2026, 8:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d110107c4c819091037d83362b0021 |
completed | April 4, 2026, 1:20 p.m. |
Created at: March 30, 2026, 7:25 p.m.