Triple
T7439234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ordre de la Libération |
E171702
|
entity |
| Predicate | numberOfCommunesRecipients |
P45298
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Ordre de la Libération, numberOfCommunesRecipients, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCommunesRecipients Context triple: [Ordre de la Libération, numberOfCommunesRecipients, 5]
-
A.
totalCommunesRecipients
chosen
Indicates the total number of communes that receive or are designated as recipients in the specified context.
-
B.
totalRecipients
Indicates the total number of distinct entities that receive something in the context of the described relationship or action.
-
C.
hasCommune
Indicates a relationship where an entity is associated with, belongs to, or is located within a specific commune (municipal administrative unit).
-
D.
numberOfParishes
Indicates the total count of parishes associated with a given entity.
-
E.
numberOfCommunitiesRepresented
Indicates the count of distinct communities that are represented in relation to a given entity or context.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34c28648190a426b5d7623b41e8 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.