Triple
T3694131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Gage |
E78413
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gage |
E26199
|
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: Gage | Statement: [Henry Gage, familyName, Gage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gage Context triple: [Henry Gage, familyName, Gage]
-
A.
Gage
chosen
Gage is a surname of English origin borne by various notable individuals, including historical and contemporary figures.
-
B.
Gordon
Gordon is the middle name of the famed Romantic poet Lord Byron, whose full name is George Gordon Byron.
-
C.
Gordon
Gordon is a small village in the Scottish Borders region of southeastern Scotland, historically part of Berwickshire.
-
D.
Garrett
Garrett is a masculine given name of Old French and Germanic origin, commonly used in English-speaking countries.
-
E.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e9e4748190aa178692ef27e3a6 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3d0f2d88190b31e8c336f1a1bf3 |
completed | March 14, 2026, 2:11 a.m. |
Created at: March 8, 2026, 3:26 p.m.