Triple
T2096779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IND Crosstown Line |
E36999
|
entity |
| Predicate | usesLetterColor |
P34374
|
FINISHED |
| Object | G |
—
|
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: G | Statement: [IND Crosstown Line, usesLetterColor, G]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLetterColor Context triple: [IND Crosstown Line, usesLetterColor, G]
-
A.
lineLetterColorStandard
chosen
Indicates the standard or default color assigned to the letter representation of a particular line.
-
B.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
C.
laterCaseColor
Indicates that the color of an entity’s case at a later time or stage in a sequence is being specified or related to another case color.
-
D.
crestColor
Indicates the color characteristic of an entity’s crest.
-
E.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba9cb84481909fe0a66c020b8864 |
completed | March 7, 2026, 5:41 a.m. |
| PD | Predicate disambiguation | batch_69abb7b6274081909df36cd7a7c6a675 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:43 p.m.