Triple
T18979433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallabong tangerine |
E464380
|
entity |
| Predicate | hasShapeFeature |
P82774
|
FINISHED |
| Object | distinctive bump at the top |
—
|
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: distinctive bump at the top | Statement: [Hallabong tangerine, hasShapeFeature, distinctive bump at the top]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShapeFeature Context triple: [Hallabong tangerine, hasShapeFeature, distinctive bump at the top]
-
A.
hasShapeModel
Indicates that an entity is associated with a specific geometric or structural shape model that represents its form.
-
B.
hasHemShape
Indicates that an item possesses a specific form or contour of its hem or lower edge.
-
C.
hasSectionShape
Indicates that one entity possesses or is characterized by a particular cross-sectional shape specified by another entity.
-
D.
hasDistinctiveShape
chosen
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
E.
hasSilhouetteShape
Indicates that one entity has the overall outline or contour shape specified or characterized by another 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65b573881908575e61a62b70787 |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.