Triple
T1008849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Far Rockaway Branch |
E21773
|
entity |
| Predicate | hasGradeCrossings |
P23561
|
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: [Far Rockaway Branch, hasGradeCrossings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGradeCrossings Context triple: [Far Rockaway Branch, hasGradeCrossings, yes]
-
A.
hasAtGradeCrossingNearby
Indicates that one entity (typically a location or segment) has a nearby at-grade crossing where two transportation paths intersect at the same level.
-
B.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
C.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
D.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
E.
hasMaximumGradeBeforeCurves
Indicates that an entity’s highest achievable grade is specified prior to any grading curves or adjustments being applied.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7f4c66c8190b6098fb72c1465a3 |
completed | March 1, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69a4b7203124819091de68cba5f731c1 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7f2d1b081908eb2df54e91c8c1d |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:41 p.m.