Triple
T17671049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brighton Beach |
E440520
|
entity |
| Predicate | stationColor |
P75847
|
FINISHED |
| Object | orange (B line bullet) |
—
|
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: orange (B line bullet) | Statement: [Brighton Beach, stationColor, orange (B line bullet)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationColor Context triple: [Brighton Beach, stationColor, orange (B line bullet)]
-
A.
stationName
Indicates the name assigned to a particular station in the relationship.
-
B.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
C.
stationType
Indicates the specific category or classification of a station based on its function, services, or operational characteristics.
-
D.
metroSystemColor
chosen
Indicates the color assigned to a metro or subway line within a transit system.
-
E.
terminusStation
Indicates that a station serves as the final endpoint or terminal stop for a given route or service.
- 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_69d8b9e87e18819087104a44dc4dc5b1 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e46f68a038819084828ff73bcf1fcc |
completed | April 19, 2026, 6 a.m. |
| PD | Predicate disambiguation | batch_69e3cde007d8819090dd92eea9f022cc |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 9:59 a.m.