Triple
T27341638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ik Kil cenote |
E684118
|
entity |
| Predicate | hasDiameterApprox |
P7302
|
FINISHED |
| Object | about 60 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 60 meters | Statement: [Ik Kil cenote, hasDiameterApprox, about 60 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiameterApprox Context triple: [Ik Kil cenote, hasDiameterApprox, about 60 meters]
-
A.
approximateDiameter
chosen
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
B.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
C.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
D.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
E.
bodyDiameter
Indicates the measurement of how wide an object's body is across its broadest cross-section.
- 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_69ef1480a76481908684256ddd5bfda3 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: April 27, 2026, 11:43 a.m.