Triple
T13202709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croix de la Libération |
E314279
|
entity |
| Predicate | numberOfCommunityRecipients |
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: [Croix de la Libération, numberOfCommunityRecipients, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCommunityRecipients Context triple: [Croix de la Libération, numberOfCommunityRecipients, 5]
-
A.
totalRecipients
Indicates the total number of distinct entities that receive something in the context of the described relationship or action.
-
B.
numberOfCommunitiesRepresented
Indicates the count of distinct communities that are represented in relation to a given entity or context.
-
C.
totalCommunesRecipients
chosen
Indicates the total number of communes that receive or are designated as recipients in the specified context.
-
D.
numberOfRecipientsPerMonth
Indicates the quantity of recipients associated with an entity for each month.
-
E.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:16 p.m.