Triple
T35740066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forest's Elbow |
E1033008
|
entity |
| Predicate | trackSection |
P155685
|
FINISHED |
| Object | tight corner |
—
|
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: tight corner | Statement: [Forest's Elbow, trackSection, tight corner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackSection Context triple: [Forest's Elbow, trackSection, tight corner]
-
A.
trackSegment
chosen
Indicates a specific portion or section of a larger track or route that is treated as a distinct segment.
-
B.
tracksSector
Indicates that one entity monitors, follows, or keeps records of the status or performance of a particular sector.
-
C.
trackFeature
Indicates that one entity monitors, records, or follows the behavior, state, or evolution of a particular feature associated with another entity.
-
D.
trackedSegment
Indicates that a specific segment or portion of something (such as a path, process, or sequence) is being monitored, recorded, or followed over time.
-
E.
track
Indicates that one entity follows, monitors, or keeps a record of another entity’s state, behavior, or progress over time.
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:06 p.m.