Triple
T7297053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Needham Line |
E164549
|
entity |
| Predicate | lineColorInformal |
P34402
|
FINISHED |
| Object | purple (MBTA Commuter Rail color) |
—
|
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: purple (MBTA Commuter Rail color) | Statement: [Needham Line, lineColorInformal, purple (MBTA Commuter Rail color)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineColorInformal Context triple: [Needham Line, lineColorInformal, purple (MBTA Commuter Rail color)]
-
A.
lineLetterColorStandard
Indicates the standard or default color assigned to the letter representation of a particular line.
-
B.
networkColorOfLine
chosen
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
C.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
-
E.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8e48d48190ada4d507f3b61bc4 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.