Triple
T33074810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opéra (Paris Métro) |
E846329
|
entity |
| Predicate | line3PlatformsType |
P175774
|
FINISHED |
| Object | side platforms |
—
|
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: side platforms | Statement: [Opéra (Paris Métro), line3PlatformsType, side platforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: line3PlatformsType Context triple: [Opéra (Paris Métro), line3PlatformsType, side platforms]
-
A.
line3PlatformLocation
Indicates the specific platform location associated with line 3 in a transit or rail system.
-
B.
line1PlatformsOpened
Indicates that the platforms serving line 1 have been opened and are available for use.
-
C.
line4PlatformsOpened
Indicates that the platforms associated with line 4 have been opened for use or made operational.
-
D.
hasRailPlatforms
Indicates that an entity is equipped with one or more rail platforms used for boarding or alighting from trains.
-
E.
hasConventionalLinePlatform
Indicates that an entity provides or is associated with a platform specifically designated for conventional (non-high-speed or standard) railway lines.
- 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d6a482fc8190b526291cd99b8696 |
completed | May 3, 2026, 5:01 a.m. |
Created at: May 1, 2026, 1:25 a.m.