Triple
T2306408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Pierre Serre |
E51848
|
entity |
| Predicate | FieldsMedalYear |
P8111
|
FINISHED |
| Object | 1954 |
—
|
LITERAL 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: 1954 | Statement: [Jean-Pierre Serre, FieldsMedalYear, 1954]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FieldsMedalYear Context triple: [Jean-Pierre Serre, FieldsMedalYear, 1954]
-
A.
militaryAward
Indicates that an entity has received or been granted a specific military honor, decoration, or award.
-
B.
medalAwardedToWinner
Indicates that a medal is given to the entity that has won a competition or contest.
-
C.
yearHonored
chosen
Indicates the specific year in which an entity received an honor, award, or formal recognition.
-
D.
peacetimeAward
Indicates that an award or honor is given during a period of peace rather than during wartime or active conflict.
-
E.
battleHonors
Indicates that an entity has been awarded or is associated with specific honors or distinctions earned through participation in battles or military engagements.
- F. None of above.
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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.