Triple
T11461527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madeleine |
E271670
|
entity |
| Predicate | tracksForLine12 |
P6301
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Madeleine, tracksForLine12, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tracksForLine12 Context triple: [Madeleine, tracksForLine12, 2]
-
A.
subwayLine
Indicates that there is a subway line connection or service relationship between the referenced entities.
-
B.
monorailLines
Indicates that there is a monorail transit line or system associated with, serving, or present in the referenced entity.
-
C.
metroLineColor
Indicates the color assigned to a specific metro or subway line in a transit system.
-
D.
lineName
Indicates the specific name or designation assigned to a particular line (such as a route, path, or service) that distinguishes it from other lines.
-
E.
lineServed
chosen
Indicates that a particular transportation line (such as a bus, train, or metro line) provides service to or is operated at a given stop, station, or route segment.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f384f08190b1150ed1389dd31a |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.