Triple
T11688169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Gray |
E277797
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Fred |
E892115
|
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: Fred | Statement: [Fred Gray, givenName, Fred]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Context triple: [Fred Gray, givenName, Fred]
-
A.
Fred
Fred is a French luxury jewelry brand renowned for its elegant, contemporary designs and high-end craftsmanship, owned by the LVMH group.
-
B.
Fred
Fred is a prolific Brazilian striker best known for his goal-scoring exploits with Fluminense and the Brazilian national team.
-
C.
Fred
Fred is the given name of Fred J. Koenekamp, an American cinematographer known for his work on films such as "Patton" and "The Towering Inferno."
-
D.
Fred
Fred is the given name of Fredro Starr, an American rapper and actor best known as a member of the hip hop group Onyx and for his roles in film and television.
-
E.
Fred
chosen
Fred is a masculine given name commonly used in English-speaking countries, often as a short form of Frederick or Alfred.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4654be881909bd0256cf18e25de |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef14431f3c81908af9167c46f8c2bc |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.