Triple
T26351036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Himba |
E662900
|
entity |
| Predicate | hairstyleSignificance |
P74257
|
FINISHED |
| Object | indicates marital status |
—
|
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: indicates marital status | Statement: [Himba, hairstyleSignificance, indicates marital status]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairstyleSignificance Context triple: [Himba, hairstyleSignificance, indicates marital status]
-
A.
hairAsSymbol
chosen
Indicates that hair functions as a symbolic element representing ideas, traits, or meanings beyond its literal physical presence.
-
B.
hasHairstyleTradition
Indicates a relationship where an entity follows, practices, or is associated with a particular traditional hairstyle.
-
C.
hairStyleInMedia
Indicates that a particular hairstyle is depicted or represented in a specific media work or context.
-
D.
stylisticSignificance
Indicates that one entity holds importance or meaning specifically because of its style or manner of expression in relation to another entity or context.
-
E.
haircutNamedAfter
Indicates that a particular hairstyle is named after a specific person, character, place, or other 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_69ee8130fc44819094e5ab1da201cd7b |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60feb75a08190be5002cfacabce78 |
completed | May 2, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 10:45 p.m.