Triple
T12171700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Dempsey |
E289982
|
entity |
| Predicate | opponent |
P437
|
FINISHED |
| Object | Georges Carpentier |
E751228
|
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: Georges Carpentier | Statement: [Jack Dempsey, opponent, Georges Carpentier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Georges Carpentier Context triple: [Jack Dempsey, opponent, Georges Carpentier]
-
A.
Georges Carpentier
chosen
Georges Carpentier was a celebrated French boxer of the early 20th century who became a world light heavyweight champion and later appeared in films and entertainment.
-
B.
George Métivier
George Métivier was a 19th-century Guernsey poet celebrated as one of the foremost writers in the Guernésiais language and often called the island’s national poet.
-
C.
Marcel Cerdan
Marcel Cerdan was a celebrated French professional boxer, widely regarded as one of France’s greatest fighters and a former world middleweight champion.
-
D.
Daniel Mendoza
Daniel Mendoza is an actor known for his role in the British comedy-drama film "Suzie Gold."
-
E.
René Cerdan
René Cerdan is known primarily as the son of legendary French-Moroccan world middleweight boxing champion Marcel Cerdan.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915dab42881908e2580c631d4d1cf |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6a6de3081908e5e0030c081d5a4 |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:50 p.m.