Triple
T36494824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estació de França |
E899154
|
entity |
| Predicate | hasStandardGaugeTracks |
P202015
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Estació de França, hasStandardGaugeTracks, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardGaugeTracks Context triple: [Estació de França, hasStandardGaugeTracks, false]
-
A.
formerTrackGauge
Indicates that an entity previously had a specified track gauge, which has since been changed or is no longer in use.
-
B.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
-
C.
isLongTrack
Indicates that something (such as a route, path, or recording) has a relatively great length or duration compared to typical or standard examples of its kind.
-
D.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
E.
hasBreakOfGaugeWith
Indicates that two connected railway lines or networks meet at a point where their track gauges differ, requiring a change of trains or transfer of cargo.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a0045a7b4c081908e4dedabda7cf790 |
completed | May 10, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_6a0042b148a48190974b173f352e4b7f |
completed | May 10, 2026, 8:32 a.m. |
| PDg | Predicate description generation | batch_6a0045a6ce788190913fa017097a15b8 |
completed | May 10, 2026, 8:45 a.m. |
Created at: May 3, 2026, 4:10 p.m.