Triple
T35250319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISS Enterprise |
E1018075
|
entity |
| Predicate | costumeAndSetDifferencesFrom |
P182989
|
FINISHED |
| Object | USS Enterprise (NCC-1701) |
—
|
NE NERFINISHED |
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: USS Enterprise (NCC-1701) | Statement: [ISS Enterprise, costumeAndSetDifferencesFrom, USS Enterprise (NCC-1701)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeAndSetDifferencesFrom Context triple: [ISS Enterprise, costumeAndSetDifferencesFrom, USS Enterprise (NCC-1701)]
-
A.
costumeContext
Indicates the situational or narrative context in which a costume is used, such as the event, setting, or role it is associated with.
-
B.
costumeFeatures
Indicates that a costume possesses or includes specific features, attributes, or decorative elements.
-
C.
costumeDesignEmphasisOn
Indicates that a costume design places particular focus or priority on a specified element, style, feature, or thematic aspect.
-
D.
costume
Indicates that one entity is wearing, dressed in, or outfitted with the other entity as a costume.
-
E.
usesCostumeDesignBasedOn
Indicates that one entity employs or incorporates the costume design concepts, styles, or elements derived from another entity as a basis for its own costume design.
- F. None of above. chosen
Provenance (4 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_69f76de407d081909dfc3c419817ae93 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f795b5228c8190adb5bf86e581f70c |
completed | May 3, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f79527c7bc8190a69d87bec01f65c8 |
completed | May 3, 2026, 6:34 p.m. |
Created at: May 3, 2026, 4:02 p.m.