Triple
T7081659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hôtel de Ville (Paris Métro) |
E164969
|
entity |
| Predicate | line11PlatformsOpeningDate |
P74874
|
FINISHED |
| Object | 1935-04-28 |
—
|
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: 1935-04-28 | Statement: [Hôtel de Ville (Paris Métro), line11PlatformsOpeningDate, 1935-04-28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: line11PlatformsOpeningDate Context triple: [Hôtel de Ville (Paris Métro), line11PlatformsOpeningDate, 1935-04-28]
-
A.
line9PlatformsOpeningDate
Indicates the date on which the platforms for line 9 were first opened for use.
-
B.
line10OpeningDate
Indicates the date on which line 10 was first opened or began operation.
-
C.
line13OpeningDate
Indicates the date on which line 13 was officially opened or began operation.
-
D.
line5OpeningDate
Indicates the date on which line 5 was first opened or began operation.
-
E.
line3OpeningDate
Indicates the calendar date on which the third line (e.g., a route, service line, or similar system component) was officially opened or began operation.
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4f1f5748190b214856bcfc70d81 |
completed | March 27, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:40 p.m.