Triple
T25223834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Violet Jones |
E632037
|
entity |
| Predicate | hairTheme |
P74257
|
FINISHED |
| Object | undergoes a major change involving cutting off her hair |
—
|
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: undergoes a major change involving cutting off her hair | Statement: [Violet Jones, hairTheme, undergoes a major change involving cutting off her hair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairTheme Context triple: [Violet Jones, hairTheme, undergoes a major change involving cutting off her hair]
-
A.
maneColor
Indicates the color attribute specifically of an entity’s mane.
-
B.
hairType
Indicates the specific kind or category of hair an entity has, such as its texture, style, or structural type.
-
C.
hairAsSymbol
chosen
Indicates that hair functions as a symbolic element representing ideas, traits, or meanings beyond its literal physical presence.
-
D.
hairColorTrait
Indicates a relationship where an entity possesses a specific hair color as a distinguishing trait.
-
E.
hairSpecialty
Indicates a professional focus or expertise in working with a particular type, style, or treatment of hair.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f47cc23da88190bad7b9a28e09898b |
completed | May 1, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f44d849e7c81909945438f40e35362 |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 21, 2026, 1:03 p.m.