Triple
T38387241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mélisande |
E899609
|
entity |
| Predicate | hasHairDescription |
P16252
|
FINISHED |
| Object | very long 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: very long hair | Statement: [Mélisande, hasHairDescription, very long hair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHairDescription Context triple: [Mélisande, hasHairDescription, very long hair]
-
A.
hasHair
Indicates that an entity possesses hair as a physical attribute.
-
B.
hairType
Indicates the specific kind or category of hair an entity has, such as its texture, style, or structural type.
-
C.
hairDetail
chosen
Indicates a relationship that specifies particular characteristics or attributes of an entity’s hair, such as style, color, length, or texture.
-
D.
hairAsSymbol
Indicates that hair functions as a symbolic element representing ideas, traits, or meanings beyond its literal physical presence.
-
E.
typicalHairMaterial
Indicates the material that hair is typically composed of for an 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_69f76e5c9b808190b486523f5c2f817d |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:31 p.m.