Triple
T16238355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G (New York City Subway service) |
E394173
|
entity |
| Predicate | serviceLetterIntroduced |
P16163
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [G (New York City Subway service), serviceLetterIntroduced, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceLetterIntroduced Context triple: [G (New York City Subway service), serviceLetterIntroduced, 1930s]
-
A.
serviceIntroduced
chosen
Indicates that a particular service has been launched, made available, or brought into operation at a certain time or context.
-
B.
usesLetteredServices
Indicates that an entity makes use of services that are identified or categorized by letter-based designations.
-
C.
introducedForServiceWith
Indicates that one entity was presented or brought to the attention of another entity specifically for the purpose of providing a service.
-
D.
serviceLabel
Indicates that a label or descriptive tag is assigned to a service to identify or categorize it.
-
E.
serviceNumberOrEquivalent
Indicates that one entity specifies the service number or an equivalent identifying code associated with another entity.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2455c7a3c81909e3b42edf03be43e |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.