Triple
T2896582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Subway C line |
E63953
|
entity |
| Predicate | usesLetteredDesignation |
P5539
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [New York City Subway C line, usesLetteredDesignation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLetteredDesignation Context triple: [New York City Subway C line, usesLetteredDesignation, true]
-
A.
hasLetterDesignation
chosen
Indicates that an entity is assigned or associated with a specific letter-based designation or code.
-
B.
usesServiceDesignation
Indicates that one entity adopts or applies a particular service designation associated with another entity or offering.
-
C.
hasDesignation
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
D.
usesLetteredServices
Indicates that an entity makes use of services that are identified or categorized by letter-based designations.
-
E.
canBeDesignatedBy
Indicates that one entity is capable of being assigned, labeled, or identified by another entity as its designation.
- 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_69ab4c45822c8190830c5f2bb97bcfd0 |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe08e7b248190a6bb0f6999f99c23 |
completed | March 7, 2026, 8:23 a.m. |
| PD | Predicate disambiguation | batch_69abdd17bcdc8190aa47274a50ba4ad4 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:08 p.m.