Triple
T32092503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hillary Shield |
E819632
|
entity |
| Predicate | honoursProfession |
P18120
|
FINISHED |
| Object | mountaineer |
—
|
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: mountaineer | Statement: [Hillary Shield, honoursProfession, mountaineer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoursProfession Context triple: [Hillary Shield, honoursProfession, mountaineer]
-
A.
honoursPosition
Indicates that one entity holds or is recognized with an honorary or distinguished position in relation to another entity.
-
B.
honoursTitle
Indicates that an entity holds or is designated by a formal honorific or honorary title.
-
C.
honorificDegree
Indicates that an entity has been awarded an honorary academic degree or title, typically in recognition of merit rather than completion of formal study.
-
D.
honourOf
Indicates that one entity is the source, bearer, or cause of another entity’s honor, prestige, or distinguished recognition.
-
E.
honouredPersonOccupation
chosen
Indicates that the honored person is or was associated with 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b63edd4c819093b664b38a69d7c8 |
completed | May 3, 2026, 2:43 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:25 a.m.