Triple
T4213233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maréchal de France |
E93952
|
entity |
| Predicate | lastConferredYear |
P1462
|
FINISHED |
| Object | 1984 |
—
|
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: 1984 | Statement: [Maréchal de France, lastConferredYear, 1984]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastConferredYear Context triple: [Maréchal de France, lastConferredYear, 1984]
-
A.
conferredOn
Indicates that something (such as an honor, title, degree, or benefit) has been formally granted or bestowed upon a particular entity.
-
B.
lastSittingYear
Indicates the specific year in which an entity most recently held a sitting, session, or term.
-
C.
conferredIn
Indicates that something (such as a degree, title, or honor) was formally granted or awarded within a particular context, event, or institution.
-
D.
lastAwarded
chosen
Indicates the most recent time or instance at which an entity received a particular award.
-
E.
matriculationYear
Indicates the calendar year in which an individual formally enrolled or was admitted into an educational program or institution.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.