Triple
T871164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wollaston station |
E18815
|
entity |
| Predicate | closedForRenovation |
P12551
|
FINISHED |
| Object | January 2018 |
—
|
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: January 2018 | Statement: [Wollaston station, closedForRenovation, January 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: closedForRenovation Context triple: [Wollaston station, closedForRenovation, January 2018]
-
A.
closedVenue
Indicates that a venue is not open or available for use during a given time or event.
-
B.
closedDuring
chosen
Indicates that an entity is not open or available for use during a specified time period or under certain conditions.
-
C.
closedForPassengers
Indicates that a transportation facility or vehicle is not available for use by passengers.
-
D.
brokeGroundForRenovation
Indicates that an entity initiated construction work to renovate or significantly upgrade another entity or site.
-
E.
closedIn
Indicates that one entity is enclosed, contained, or surrounded within the boundaries or limits defined by another entity.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac94d5ac81909feee876696da589 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa89ca008190b50d061ac7fe19f9 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.