Triple
T319078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gare Montparnasse |
E7771
|
entity |
| Predicate | incidentDate |
P830
|
FINISHED |
| Object | 22 October 1895 |
—
|
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: 22 October 1895 | Statement: [Gare Montparnasse, incidentDate, 22 October 1895]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: incidentDate Context triple: [Gare Montparnasse, incidentDate, 22 October 1895]
-
A.
attackDate
Indicates the calendar date on which an attack or assault event took place.
-
B.
immediateCauseDate
Indicates the specific date on which an event or condition directly caused another event or outcome to occur.
-
C.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
-
D.
date
Indicates that two entities are engaged in or participate in a romantic or social outing or relationship with each other.
-
E.
dateOfRelatedEvent
chosen
Indicates that there is a specific date on which a related event associated with the subject occurs or occurred.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.