Triple
T7439232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ordre de la Libération |
E171702
|
entity |
| Predicate | numberOfIndividualRecipients |
P40621
|
FINISHED |
| Object | 1038 |
—
|
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: 1038 | Statement: [Ordre de la Libération, numberOfIndividualRecipients, 1038]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIndividualRecipients Context triple: [Ordre de la Libération, numberOfIndividualRecipients, 1038]
-
A.
totalRecipients
Indicates the total number of distinct entities that receive something in the context of the described relationship or action.
-
B.
numberOfReceivers
chosen
Indicates the quantity of distinct receivers associated with or involved in a given entity, event, or transaction.
-
C.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
-
D.
scopeOfRecipients
Indicates the range or group of recipients to whom something (such as information, communication, or benefits) is directed or applicable.
-
E.
estimatedNumberOfBeneficiaries
Indicates the approximate count of individuals or entities expected to receive benefits from something.
- 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.