Triple
T25585649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Méndez Álvaro |
E641371
|
entity |
| Predicate | hasBusTerminalType |
P158874
|
FINISHED |
| Object | long-distance coach terminal |
—
|
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: long-distance coach terminal | Statement: [Méndez Álvaro, hasBusTerminalType, long-distance coach terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusTerminalType Context triple: [Méndez Álvaro, hasBusTerminalType, long-distance coach terminal]
-
A.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
B.
hasBusStation
Indicates that a place or area contains or is served by a bus station.
-
C.
hasBusStandType
Indicates the specific category or type of bus stand associated with a given bus stand entity.
-
D.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
E.
hasBusInterchange
Indicates that one transport-related entity includes, contains, or is associated with a bus interchange facility.
- F. None of above. chosen
Provenance (4 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f9698c3c8190b93af7d959ecd7c1 |
completed | May 2, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 4:16 p.m.