Triple
T12524744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samastipur Junction |
E299405
|
entity |
| Predicate | hasRetiringRooms |
P105703
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Samastipur Junction, hasRetiringRooms, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetiringRooms Context triple: [Samastipur Junction, hasRetiringRooms, yes]
-
A.
hasChangingRooms
Indicates that a place or facility provides designated rooms where people can change their clothes.
-
B.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
C.
hasPeriodRooms
Indicates that an entity contains rooms that are decorated or preserved to reflect specific historical periods.
-
D.
hasStateRooms
Indicates that an entity (such as a ship, building, or facility) contains or is equipped with state rooms.
-
E.
hasRetiredNumbersDisplay
Indicates that an entity features a display or presentation of numbers that have been officially retired (such as jersey numbers).
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d9540d7b788190a0d57b098e90e491 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d95f5148948190946a575d812b329d |
completed | April 10, 2026, 8:36 p.m. |
Created at: April 8, 2026, 9:57 p.m.