Triple
T1223324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Atkins mango |
E26271
|
entity |
| Predicate | hasBearingPattern |
P26005
|
FINISHED |
| Object | regular bearing under many conditions |
—
|
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: regular bearing under many conditions | Statement: [Tommy Atkins mango, hasBearingPattern, regular bearing under many conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBearingPattern Context triple: [Tommy Atkins mango, hasBearingPattern, regular bearing under many conditions]
-
A.
hasSpiralPattern
Indicates that one entity exhibits or possesses a spiral-shaped pattern or arrangement in relation to another.
-
B.
hasNotableFieldOfBearers
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
C.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
-
D.
hasBowType
Indicates that an entity possesses or is associated with a specific type or category of bow.
-
E.
kitPattern
Indicates the design or visual pattern featured on a team's kit or uniform.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be233fd88190996faf4105c0b8d7 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd3140688190ac6e24de157fd61e |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:47 p.m.