Triple
T12983411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrail |
E321705
|
entity |
| Predicate | bearerReputation |
P93104
|
FINISHED |
| Object | chevalier sans peur et sans reproche |
—
|
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: chevalier sans peur et sans reproche | Statement: [Terrail, bearerReputation, chevalier sans peur et sans reproche]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bearerReputation Context triple: [Terrail, bearerReputation, chevalier sans peur et sans reproche]
-
A.
scoringReputation
Indicates that one entity evaluates and assigns a reputation-related score to another entity based on its behavior or performance.
-
B.
liveReputation
Indicates a dynamic, continuously updated assessment of an entity’s standing, trustworthiness, or performance based on recent or real-time information.
-
C.
haveReputation
chosen
Indicates that an entity is recognized or regarded in a certain way by others, reflecting its perceived character, quality, or status.
-
D.
securityReputation
Indicates the assessed trustworthiness or risk level associated with an entity’s security posture or behavior.
-
E.
institutionalReputationContext
Indicates the situational or environmental factors that shape or influence an institution’s reputation.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:39 p.m.