Triple
T8721516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1er régiment de parachutistes d’infanterie de marine |
E207020
|
entity |
| Predicate | isProfessionalUnit |
P84265
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [1er régiment de parachutistes d’infanterie de marine, isProfessionalUnit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isProfessionalUnit Context triple: [1er régiment de parachutistes d’infanterie de marine, isProfessionalUnit, true]
-
A.
isPro
Indicates that an entity is a professional or expert in a particular field, activity, or domain.
-
B.
isUnitIn
Indicates that a specific unit is located within or belongs to a particular container, group, or context.
-
C.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
D.
isMetric
Indicates that something satisfies the properties required to be considered a metric, such as defining distances that obey non-negativity, identity, symmetry, and the triangle inequality.
-
E.
isNaturalUnit
Indicates that something is a fundamental, standard unit of measurement defined by natural constants or inherent properties rather than by arbitrary human conventions.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d03f0848190a50c77e5cd028ee7 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc489dd528819084ed5d88bd8bb3d6 |
completed | March 31, 2026, 10:20 p.m. |
Created at: March 30, 2026, 6:36 p.m.