Triple
T7491095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1955 British Kangchenjunga expedition |
E177005
|
entity |
| Predicate | respectedLocalBeliefs |
P77840
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [1955 British Kangchenjunga expedition, respectedLocalBeliefs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: respectedLocalBeliefs Context triple: [1955 British Kangchenjunga expedition, respectedLocalBeliefs, yes]
-
A.
religiousCulturalContext
Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
-
B.
religiousAttitude
Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
-
C.
mustRespect
Indicates that one entity is obligated to show respect or deference toward another entity.
-
D.
religiousReception
Indicates a relationship where one entity formally receives, welcomes, or hosts another in a specifically religious or faith-based context.
-
E.
moralBelief
Indicates that an agent holds a normative judgment about what is right, wrong, good, or bad in a given context.
- 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_69c69f2583808190bd1a4936c42a5815 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f81b431481908214b69c6c8d83bc |
completed | March 27, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d266d88190982cf5d2ee2e9564 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:43 p.m.