Triple
T33252770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Chapelle |
E851292
|
entity |
| Predicate | lineRoleOnLine2 |
P175617
|
FINISHED |
| Object | intermediate station |
—
|
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: intermediate station | Statement: [La Chapelle, lineRoleOnLine2, intermediate station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineRoleOnLine2 Context triple: [La Chapelle, lineRoleOnLine2, intermediate station]
-
A.
roleOnLine1
Indicates that an entity holds a specific role or function associated with the first line of a multi-line structure or sequence.
-
B.
lineTerminal2
Indicates that the referenced entity serves as the second terminal (endpoint) of a line.
-
C.
lineRole_Line13
Indicates that an entity serves a specific role or function within the context of Line 13.
-
D.
hasLineRole
chosen
Indicates that an entity participates in a line (such as a queue, route, or sequence) with a specific functional role or position within that line.
-
E.
lineUse
Indicates how a particular line (such as a route, track, or service line) is utilized or purposed within a system or network.
- 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_69f34963135c819084e7f1d483421f00 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db2f4b2081909fd2e59258927121 |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82fef788190b9ad19a36c0312dc |
completed | May 3, 2026, 5:08 a.m. |
Created at: May 1, 2026, 1:31 a.m.