Triple
T2377924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heathrow Express |
E46241
|
entity |
| Predicate | numberOfIntermediateStops |
P38823
|
FINISHED |
| Object | 0 |
—
|
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: 0 | Statement: [Heathrow Express, numberOfIntermediateStops, 0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfIntermediateStops Context triple: [Heathrow Express, numberOfIntermediateStops, 0]
-
A.
hasIntermediateStation
Indicates that a route, journey, or connection includes a station that lies between its starting point and its final destination.
-
B.
hasIntermediateCity
Indicates that there is a city located between two other places along a route or connection.
-
C.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
D.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
-
E.
intermediateTerminus
Indicates that something serves as a temporary or middle stopping point within a larger route, process, or sequence.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abca4c937c8190b4dfca716b868d4f |
completed | March 7, 2026, 6:48 a.m. |
Created at: March 4, 2026, 7:57 p.m.