Triple
T29005437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badarpur Border metro station |
E736416
|
entity |
| Predicate | hasEntryExit |
P89546
|
FINISHED |
| Object | multiple entry and exit gates |
—
|
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: multiple entry and exit gates | Statement: [Badarpur Border metro station, hasEntryExit, multiple entry and exit gates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntryExit Context triple: [Badarpur Border metro station, hasEntryExit, multiple entry and exit gates]
-
A.
hasExitFor
Indicates that something provides or includes a specific exit intended for a particular destination, purpose, or user.
-
B.
hasNumberOfExits
Indicates the relationship that specifies how many exits are associated with a given entity.
-
C.
hasEntryOn
Indicates that one entity contains or includes an entry, record, or listing about another entity.
-
D.
hasExitList
chosen
Indicates that an entity is associated with a collection of defined exits or exit points.
-
E.
hasNumberedExit
Indicates that an entity (such as a road or highway) includes or is associated with an exit that has an assigned number.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 28, 2026, 9:37 a.m.