Triple
T2921852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N |
E78744
|
entity |
| Predicate | trunkLineColor |
P19516
|
FINISHED |
| Object | Broadway Line color (yellow) |
—
|
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: Broadway Line color (yellow) | Statement: [N, trunkLineColor, Broadway Line color (yellow)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trunkLineColor Context triple: [N, trunkLineColor, Broadway Line color (yellow)]
-
A.
trunkLineColorRepresents
Indicates that the color of a trunk line is used to signify or encode a particular meaning, status, or category associated with that line.
-
B.
trackColor
Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
-
C.
trunkColorFamily
Indicates the general color category or family to which an object's trunk (such as a tree or vehicle trunk) belongs.
-
D.
trunkColorDesignation
chosen
Indicates the specified color assigned to the trunk of an object (such as a tree or similar structure).
-
E.
colorOfTrailMarkings
Indicates the relationship specifying what color the trail’s markings are.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:54 p.m.