Triple
T8418379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speed Stick Antiperspirant |
E198784
|
entity |
| Predicate | sweatControlArea |
P21283
|
FINISHED |
| Object | axillary region |
—
|
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: axillary region | Statement: [Speed Stick Antiperspirant, sweatControlArea, axillary region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sweatControlArea Context triple: [Speed Stick Antiperspirant, sweatControlArea, axillary region]
-
A.
areaAControl
Indicates that one entity exercises control or authority over a specified area or region.
-
B.
areaCControl
Indicates that an entity exercises control or authority over a specific geographic area or region.
-
C.
areaBControl
Indicates that one entity has control or authority over a specific region or area labeled as B.
-
D.
hasBodyRegion
chosen
Indicates that an entity possesses, includes, or is associated with a specific anatomical or bodily region.
-
E.
wetnessLevel
Indicates the degree or intensity of how wet something is in relation to a reference state or scale.
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb84c7d6e48190a2bbde89c5d42af6 |
completed | March 31, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.