Triple
T2969951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Compagnon de la Libération |
E80255
|
entity |
| Predicate | totalIndividualRecipients |
P7074
|
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: [Compagnon de la Libération, totalIndividualRecipients, 1038]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalIndividualRecipients Context triple: [Compagnon de la Libération, totalIndividualRecipients, 1038]
-
A.
totalRecipients
chosen
Indicates the total number of distinct entities that receive something in the context of the described relationship or action.
-
B.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
-
C.
locationOfRecipients
Indicates the place or geographic area where the intended recipients of something are situated.
-
D.
individualRecipient
Indicates that a specific individual is the direct recipient or beneficiary of something (such as an item, message, or action).
-
E.
scopeOfRecipients
Indicates the range or group of recipients to whom something (such as information, communication, or benefits) is directed or applicable.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad997282b481909d078be0e70d9930 |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960e71f8819088179d11248c6ed0 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.