Triple
T18807596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SL metro |
E459919
|
entity |
| Predicate | numberOfUndergroundStations |
P133501
|
FINISHED |
| Object | 47 |
—
|
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: 47 | Statement: [SL metro, numberOfUndergroundStations, 47]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUndergroundStations Context triple: [SL metro, numberOfUndergroundStations, 47]
-
A.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
B.
hasUndergroundConnections
Indicates that one entity is linked to another through subterranean or hidden passageways, networks, or channels.
-
C.
subwayStation
Indicates that one entity is a subway station associated with, located in, or serving the other entity.
-
D.
subwayStationsApprox
Indicates that one subway station is approximately located near or corresponds to another subway station, allowing for minor differences in position or naming.
-
E.
numberOfStationsOpenedInPhase1
Indicates the total count of stations that were opened during the first phase of a project or rollout.
- 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a3d8ab9c819097834eac798ce810 |
completed | April 20, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:53 a.m.