Triple
T8732707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sótano de las Golondrinas |
E207296
|
entity |
| Predicate | entranceLength |
P73716
|
FINISHED |
| Object | approximately 90 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: approximately 90 meters | Statement: [Sótano de las Golondrinas, entranceLength, approximately 90 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entranceLength Context triple: [Sótano de las Golondrinas, entranceLength, approximately 90 meters]
-
A.
entranceSize
Indicates the size or dimensions of an entrance relative to a referenced object or structure.
-
B.
entranceWidth
Indicates the measured horizontal span of an entrance opening that defines how wide the entry passage is.
-
C.
hasEntrancePassageLength
chosen
Indicates the length of an entrance passage associated with an entity.
-
D.
hasNumberOfEntrances
Indicates the relationship that specifies how many entrances an entity possesses.
-
E.
hasEntrance
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
- 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_69ca8358e4008190898471a59b96c301 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d2903b08190a5ef29b6d6ca5f1c |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:37 p.m.