Triple
T11700663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cross pattée |
E278115
|
entity |
| Predicate | hasShapeCharacteristic |
P82774
|
FINISHED |
| Object | arms narrow at the center |
—
|
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: arms narrow at the center | Statement: [cross pattée, hasShapeCharacteristic, arms narrow at the center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShapeCharacteristic Context triple: [cross pattée, hasShapeCharacteristic, arms narrow at the center]
-
A.
hasDistinctiveShape
chosen
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
B.
usesFormCharacteristic
Indicates that one entity employs or relies on a particular formal property or structural characteristic of another entity in performing an action or fulfilling a function.
-
C.
hasIrregularShape
Indicates that an entity possesses a form or outline that deviates from a regular, standard, or symmetrical shape.
-
D.
hasBillShape
Indicates that one entity has a bill whose shape matches the specified form or category.
-
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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49a025881909377c81d3debf465 |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7b30948190b616a9db5c5488d5 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.