Triple
T159018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ranger Tab |
E3239
|
entity |
| Predicate | locationOnUniform |
P6852
|
FINISHED |
| Object | upper left sleeve |
—
|
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: upper left sleeve | Statement: [Ranger Tab, locationOnUniform, upper left sleeve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOnUniform Context triple: [Ranger Tab, locationOnUniform, upper left sleeve]
-
A.
coordinateLocation
Indicates that an entity is located at, or associated with, a specific geographic coordinate or set of coordinates.
-
B.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
C.
locationVariesWith
Indicates that the location of one entity changes in dependence on, or as a function of, changes in another entity.
-
D.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a 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_69a2527757ec819090b8becb2cf1a862 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2583169a0819081b658882e5bc452 |
completed | Feb. 28, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69a25660c2a48190b4174d5e6da3cb9d |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2580b00988190868ee24c0289cf70 |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.