Triple
T30033620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puente de Occidente |
E763089
|
entity |
| Predicate | approximateMainSpan |
P25800
|
FINISHED |
| Object | about 220 meters |
—
|
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: about 220 meters | Statement: [Puente de Occidente, approximateMainSpan, about 220 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateMainSpan Context triple: [Puente de Occidente, approximateMainSpan, about 220 meters]
-
A.
hasMainSpanLength
Indicates the relationship specifying the primary or main span’s length associated with an entity.
-
B.
centralSpanLength
Indicates the length of the central portion or main span of an object or structure.
-
C.
longitudAproximada
Indicates an approximate measurement of the length of something, rather than its exact value.
-
D.
approximateLengthInMeters
chosen
Indicates the estimated or roughly measured length of something expressed in meters.
-
E.
lengthOfMainBuilding
Indicates the measured physical length of the main building in the context of a larger structure or site.
- 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_69f2246fb2b88190acff36bf7975c8f0 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: April 29, 2026, 6:50 p.m.