Triple
T38398690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elberon station |
E900834
|
entity |
| Predicate | adjacentLineDirectionNorth |
P36167
|
FINISHED |
| Object | toward Long Branch station |
—
|
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: toward Long Branch station | Statement: [Elberon station, adjacentLineDirectionNorth, toward Long Branch station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentLineDirectionNorth Context triple: [Elberon station, adjacentLineDirectionNorth, toward Long Branch station]
-
A.
adjacentCityNorth
Indicates that one city is directly to the north of another city and shares a common boundary or is immediately neighboring it in that direction.
-
B.
adjacentLine
chosen
Indicates that one line is directly next to another line, sharing a common boundary or position without overlapping.
-
C.
adjacentStationNorth
Indicates that one station is directly adjacent to another station to its north.
-
D.
hasNorthNeighbor
Indicates that one entity is located directly to the north of another entity.
-
E.
hasAdjacentStationDirectionNorthwest
Indicates that one station is directly adjacent to another in the northwest direction.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: May 3, 2026, 4:31 p.m.