Triple
T4159464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place du Maréchal Leclerc |
E91494
|
entity |
| Predicate | honoursPersonOccupation |
P18120
|
FINISHED |
| Object | military officer |
—
|
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: military officer | Statement: [Place du Maréchal Leclerc, honoursPersonOccupation, military officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoursPersonOccupation Context triple: [Place du Maréchal Leclerc, honoursPersonOccupation, military officer]
-
A.
honouredPersonOccupation
chosen
Indicates that the honored person is or was associated with a particular occupation or professional role.
-
B.
honoredPerson
Indicates that a person is the recipient of honor, recognition, or special distinction from another party or in a particular context.
-
C.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
D.
honoreeRole
Indicates the specific role, title, or capacity in which an individual is being honored in relation to an award, event, or recognition.
-
E.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0321eee88190871c1d4bf44a5007 |
completed | March 9, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69af018dc90c8190a754b1bfbc802e80 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:44 p.m.