Triple
T95962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OM |
E1930
|
entity |
| Predicate | honourType |
P4123
|
FINISHED |
| Object | order of chivalry |
—
|
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: order of chivalry | Statement: [OM, honourType, order of chivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honourType Context triple: [OM, honourType, order of chivalry]
-
A.
honors
Indicates that one entity shows respect, recognition, or esteem toward another entity, often in a formal or ceremonial way.
-
B.
honorLevel
Indicates the degree or status of respect, distinction, or recognition accorded to an entity relative to others.
-
C.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
-
D.
honourSystem
Indicates a relationship where compliance, access, or behavior is governed by trust in individuals to act honestly without direct enforcement or verification.
-
E.
honorificTitle
Indicates that one entity serves as a formal honorific or respectful title used to address or refer to 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250ca7eec8190b31f7e61f5e3ee1f |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.