Triple
T3293646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burt Young |
E69158
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gerald |
E175316
|
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: Gerald | Statement: [Burt Young, givenName, Gerald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerald Context triple: [Burt Young, givenName, Gerald]
-
A.
Gerald
Gerald is the birth name of Jerry Brown, the longtime Democratic politician and former governor of California.
-
B.
Gerald
chosen
Gerald is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
C.
Gerald
Gerald is the middle name of Stephen G. Breyer, a former Associate Justice of the United States Supreme Court.
-
D.
Gerry
Gerry is a minimalist 2002 drama film directed by Gus Van Sant, starring Matt Damon and Casey Affleck as two friends lost in the desert.
-
E.
Gerry
Gerry is a fictional character played by Irish actor Ciarán Hinds, known from his work in film and television dramas.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb074f35081909dd3c8a09544b5f1 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e86b8e04819091f4a4ae6d6a87ad |
completed | March 12, 2026, 4:23 p.m. |
Created at: March 8, 2026, 3:10 p.m.