Triple
T36939125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas State Highway 99 |
E913701
|
entity |
| Predicate | isTollRoadForMostSegments |
P186713
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Texas State Highway 99, isTollRoadForMostSegments, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTollRoadForMostSegments Context triple: [Texas State Highway 99, isTollRoadForMostSegments, true]
-
A.
hasTollSegment
Indicates that a route, road, or path includes a segment where a toll must be paid.
-
B.
isTollRoadDestination
Indicates that a location serves as a destination reachable via a toll road or requiring travel on a toll road to access it.
-
C.
tollRoadOf
Indicates that a road segment is a toll road belonging to or associated with a particular roadway, route, or transportation network.
-
D.
hasTollBoothsAt
Indicates that toll booths are present at or associated with a particular location or segment of infrastructure.
-
E.
isTollFacilityOf
Indicates that a facility (such as a toll booth, plaza, or gantry) is part of, or used to collect tolls for, a specific toll road or toll transportation infrastructure.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:13 p.m.