Triple
T21046151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sty Head Pass |
E518455
|
entity |
| Predicate | hasEmergencyFeature |
P142603
|
FINISHED |
| Object | Sty Head stretcher box |
—
|
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: Sty Head stretcher box | Statement: [Sty Head Pass, hasEmergencyFeature, Sty Head stretcher box]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyFeature Context triple: [Sty Head Pass, hasEmergencyFeature, Sty Head stretcher box]
-
A.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
B.
hasEmergencyAlarm
Indicates that an entity is equipped with or associated with an emergency alarm system that can be activated in urgent situations.
-
C.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
D.
hasEmergencyLevel
Indicates that an entity is associated with a specific degree or severity of emergency status.
-
E.
supportsEmergencySOS
Indicates that one entity provides or is compatible with an emergency SOS function or service for another entity.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcf3cac081909915a440fbb5c084 |
completed | April 21, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2df1a888190b5b478e76bdf7fdf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:33 p.m.