Triple
T3752117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard |
E81355
|
entity |
| Predicate | servedByLine |
P1293
|
FINISHED |
| Object | Yellow Line |
E14071
|
NE 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: Yellow Line | Statement: [Howard, servedByLine, Yellow Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yellow Line Context triple: [Howard, servedByLine, Yellow Line]
-
A.
Yellow Line
The Yellow Line is a major corridor of Bengaluru’s Namma Metro system designed to improve north–south connectivity across the city.
-
B.
Yellow Line
chosen
The Yellow Line is one of the color-coded rapid transit routes in the Washington Metro system, running primarily in a north–south direction and serving key areas in Washington, D.C. and Northern Virginia.
-
C.
Yellow Line
The Yellow Line is one of the primary passenger rail routes of the Tyne and Wear Metro rapid transit system serving the Newcastle upon Tyne area in North East England.
-
D.
Yellow Line
The Yellow Line is one of the main lines of the Lisbon Metro system, connecting key residential and commercial areas of Portugal’s capital.
-
E.
Yellow Line
Yellow Line is one of the major rapid transit corridors of the Delhi Metro network, connecting key areas across Delhi and its neighboring regions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb92135c819093f6d616d3ad28ff |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b316140819089c90f3e2bd81ad8 |
completed | March 14, 2026, 2:05 p.m. |
Created at: March 8, 2026, 3:35 p.m.