Triple
T8084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SHASS |
E160
|
entity |
| Predicate | hasComponentTerm |
P35
|
FINISHED |
| Object | Humanities |
—
|
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: Humanities | Statement: [SHASS, hasComponentTerm, Humanities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComponentTerm Context triple: [SHASS, hasComponentTerm, Humanities]
-
A.
hasPart
chosen
Indicates that one entity is a component, segment, or constituent part of another entity.
-
B.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
C.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
D.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
E.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2407916ac8190b76d2e6690efaef3 |
completed | Feb. 28, 2026, 1:10 a.m. |
| PD | Predicate disambiguation | batch_69a23fe3a87881909ab95bb3a0b474ec |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.