Triple
T31639998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LGV network in France |
E807421
|
entity |
| Predicate | speedRecordTrain |
P58444
|
FINISHED |
| Object | TGV V150 |
—
|
NE NERFINISHED |
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: TGV V150 | Statement: [LGV network in France, speedRecordTrain, TGV V150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speedRecordTrain Context triple: [LGV network in France, speedRecordTrain, TGV V150]
-
A.
maximumSpeedRecord
chosen
Indicates that an entity holds the highest recorded speed value (a speed record) within a given context or category.
-
B.
speedOfHighSpeedTrain
Indicates the velocity at which a high-speed train is traveling.
-
C.
worldSpeedRecordContext
Indicates the contextual circumstances (such as event, conditions, or category) under which a world speed record is set or recognized.
-
D.
peacetimeSpeedRecord
Indicates the maximum speed achieved under non-combat, peacetime conditions, recognized as a record.
-
E.
worldSpeedRecordLocation
Indicates the location where a world speed record was achieved or officially recorded.
- 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_69f348d9ce58819093ea2da83cbeeec1 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 10:49 p.m.