Triple
T9878529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alliigator Tears |
E240140
|
entity |
| Predicate | primaryGenreInfluence |
P20936
|
FINISHED |
| Object | country |
—
|
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: country | Statement: [Alliigator Tears, primaryGenreInfluence, country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryGenreInfluence Context triple: [Alliigator Tears, primaryGenreInfluence, country]
-
A.
hasGenreInfluenceOn
Indicates that one genre has a notable impact on shaping or influencing the characteristics, style, or development of another genre.
-
B.
influencedByGenre
chosen
Indicates that something’s characteristics, style, or development are shaped or affected by a particular genre.
-
C.
primaryInfluence
Indicates that one entity serves as the main or most significant influencing factor on another entity’s state, behavior, or outcome.
-
D.
usedGenre
Indicates that one entity employs or is associated with a particular genre in its creation, presentation, or classification.
-
E.
mainGenreShiftTo
Indicates a change in the primary genre classification of something from one main genre to another.
- 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb4135c108190b3330e929509699d |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:37 p.m.