Triple
T7261528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paso Icalma |
E159664
|
entity |
| Predicate | hasCrossingType |
P10712
|
FINISHED |
| Object | road border crossing |
—
|
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: road border crossing | Statement: [Paso Icalma, hasCrossingType, road border crossing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossingType Context triple: [Paso Icalma, hasCrossingType, road border crossing]
-
A.
crossingType
chosen
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
B.
hasTypeOfCross
Indicates that an entity possesses or is associated with a specific type or style of cross.
-
C.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
D.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
E.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:57 p.m.