Triple
T12010686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | François Sevez |
E285895
|
entity |
| Predicate | serviceNumberOrEquivalent |
P102647
|
FINISHED |
| Object | French officer corps |
—
|
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: French officer corps | Statement: [François Sevez, serviceNumberOrEquivalent, French officer corps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceNumberOrEquivalent Context triple: [François Sevez, serviceNumberOrEquivalent, French officer corps]
-
A.
serviceNumber
Indicates a unique identifying number assigned to a service, used to reference, track, or distinguish that service from others.
-
B.
serviceNumberLabel
Indicates that a label or identifier is assigned to denote the service number associated with an entity.
-
C.
serviceNumberApproximate
Indicates that one entity’s service number is approximately equal to, but not necessarily exactly the same as, another entity’s service number.
-
D.
serviceNumbering
Indicates that a specific service is assigned or associated with a particular identifying number or code.
-
E.
serviceNumberOrClass
Indicates that one entity specifies the service identifier or class designation associated with another entity.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903d7777481908cd5a001f75e2ee3 |
completed | April 10, 2026, 2:06 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d9038e39f881908c58c19802ba2eb0 |
completed | April 10, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:46 p.m.