Triple
T34694372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Headstone Lane |
E890985
|
entity |
| Predicate | hasStationEntranceFrom |
P1974
|
FINISHED |
| Object | Headstone Lane road |
—
|
NE NERFINISHED |
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: Headstone Lane road | Statement: [Headstone Lane, hasStationEntranceFrom, Headstone Lane road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStationEntranceFrom Context triple: [Headstone Lane, hasStationEntranceFrom, Headstone Lane road]
-
A.
hasEntranceOn
chosen
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
B.
hasSubwayStationEntrance
Indicates that one entity serves as an entrance or access point to a subway station associated with another entity.
-
C.
hasNearbyUndergroundStationEntrance
Indicates that one entity is located close to an entrance of an underground (subway/metro) station.
-
D.
isSecondaryEntranceOf
Indicates that one entrance serves as an additional or subordinate access point to a primary entrance of the same place or structure.
-
E.
hasEntrance
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffb69812808190a751853b30183e65 |
completed | May 9, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69ffb63bdda88190a9dd8426dc0bad43 |
completed | May 9, 2026, 10:33 p.m. |
Created at: May 1, 2026, 2:05 a.m.