Triple
T29060549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villejuif – Léo Lagrange |
E735515
|
entity |
| Predicate | followingStationOnLine7 |
P187040
|
FINISHED |
| Object | Villejuif – Paul Vaillant-Couturier |
—
|
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: Villejuif – Paul Vaillant-Couturier | Statement: [Villejuif – Léo Lagrange, followingStationOnLine7, Villejuif – Paul Vaillant-Couturier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followingStationOnLine7 Context triple: [Villejuif – Léo Lagrange, followingStationOnLine7, Villejuif – Paul Vaillant-Couturier]
-
A.
followingStationOnLineD
Indicates that one station is the next station in sequence after another station on subway line D.
-
B.
followedByStationOnLine1
Indicates that one station directly succeeds another station along the sequence of stops on Line 1.
-
C.
followedByStationOnLineM2
Indicates that one station is immediately followed by another station along metro line M2 in the direction of travel.
-
D.
followingStationOnYellowLine
Indicates that one station is the next station in sequence after another on the Yellow Line.
-
E.
followingStationOnRedLine
Indicates that one station is the next station immediately following another station along the Red Line route.
- 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_69f077e85498819088b65186550da8cd |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb3424724c8190ba55ecf66fa0b171 |
completed | May 6, 2026, 12:29 p.m. |
Created at: April 28, 2026, 10:15 a.m.