Triple
T9860334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ulitsa Akademika Yangelya |
E239692
|
entity |
| Predicate | servesLineNumber |
P1293
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [Ulitsa Akademika Yangelya, servesLineNumber, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesLineNumber Context triple: [Ulitsa Akademika Yangelya, servesLineNumber, 9]
-
A.
servesLine
Indicates that a transportation stop, station, or facility is on and provides service for a particular transit line.
-
B.
servesLineTo
Indicates that one entity provides or operates a particular service line or route for another entity or location.
-
C.
servesLineSince
Indicates that a transportation service or route has been operating on a particular line since a specified point in time.
-
D.
lineServed
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.
-
E.
servedByLine
chosen
Indicates that a transportation stop, station, or location is provided service by a specific transit line.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3b582cc81909a6d638fe2573c43 |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:35 p.m.