Triple
T10192417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvetot |
E238068
|
entity |
| Predicate | distanceToLeHavre |
P92619
|
FINISHED |
| Object | approximately 50 km northeast |
—
|
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: approximately 50 km northeast | Statement: [Yvetot, distanceToLeHavre, approximately 50 km northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLeHavre Context triple: [Yvetot, distanceToLeHavre, approximately 50 km northeast]
-
A.
distanceFromCalais
Indicates the measured distance separating a given place or object from the location of Calais.
-
B.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
C.
distanceToMarseilleKilometers
Indicates the physical distance, measured in kilometers, between a given location or entity and the city of Marseille.
-
D.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
E.
endingStationInLeHavre
Indicates that an event or route concludes at a station located in Le Havre.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedc4fb808190aae2e4b84be96f83 |
completed | April 2, 2026, 4:17 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69cd7edc6cf081909d95859d880a4059 |
completed | April 1, 2026, 8:23 p.m. |
Created at: March 30, 2026, 9:13 p.m.