Triple
T13521144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexican Federal Highway 40 |
E322896
|
entity |
| Predicate | hasFreeSegment |
P102825
|
FINISHED |
| Object | libre (free) road |
—
|
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: libre (free) road | Statement: [Mexican Federal Highway 40, hasFreeSegment, libre (free) road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFreeSegment Context triple: [Mexican Federal Highway 40, hasFreeSegment, libre (free) road]
-
A.
hasFreeEntry
Indicates that access to something (such as an event, place, or service) does not require payment of an entry fee.
-
B.
hasFreeZone
Indicates that an entity includes or is associated with a designated free zone area where special rules, privileges, or exemptions apply.
-
C.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
D.
hasRegularSegment
Indicates that an entity includes or is associated with a segment that occurs in a consistent, repeating, or standard pattern.
-
E.
hasSegmentStatus
chosen
Indicates that a specific segment within a larger whole is associated with a particular status or condition.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa3df0c8190804174695587f0ea |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.