Triple
T16646947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Raincoats |
E404491
|
entity |
| Predicate | hasDIYAesthetic |
P102534
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Raincoats, hasDIYAesthetic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDIYAesthetic Context triple: [The Raincoats, hasDIYAesthetic, true]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
hasNotableDiorama
Indicates that an entity features or includes a diorama that is considered notable or significant.
-
C.
hasCraft
Indicates a relationship where an entity possesses, operates, or is associated with a particular vehicle, vessel, or other craft.
-
D.
hasDesigned
Indicates that one entity is the creator or designer of another entity.
-
E.
associatedAesthetic
chosen
Indicates a relationship where one entity is linked to or characterized by a particular aesthetic style, quality, or visual/theme-based sensibility.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad66fe88190be582b81719f2ac1 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.