Triple
T23971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Subway |
E474
|
entity |
| Predicate | safetyFeature |
P642
|
FINISHED |
| Object | emergency intercoms on platforms |
—
|
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: emergency intercoms on platforms | Statement: [New York City Subway, safetyFeature, emergency intercoms on platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyFeature Context triple: [New York City Subway, safetyFeature, emergency intercoms on platforms]
-
A.
protects
Indicates taking action to keep someone or something safe from harm, danger, or negative effects.
-
B.
protectedBy
Indicates that one entity provides protection, defense, or safeguarding for another entity.
-
C.
hasNotableFeature
chosen
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
security
Indicates that an entity provides protection, safety measures, or safeguards to another entity or against specific threats or risks.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.