Triple
T67383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the French Republic |
E1342
|
entity |
| Predicate | previousTermLengthChangedIn |
P4214
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [President of the French Republic, previousTermLengthChangedIn, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousTermLengthChangedIn Context triple: [President of the French Republic, previousTermLengthChangedIn, 2000]
-
A.
termLength
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
B.
previousTitle
Indicates that one title held or used by an entity directly preceded another title in sequence or time.
-
C.
usedSince
Indicates that an entity has been in use starting from a specified point in time and continuing thereafter.
-
D.
hasTerm
Indicates that an entity includes, is associated with, or is defined by a specific term or condition.
-
E.
legislativePeriod
Indicates the specific legislative term or session during which an action, event, or status is valid or took place.
- F. None of above. chosen
Provenance (4 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2509a1c088190b4afa3045455709a |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.