Triple
T19919491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuevas de Mármol |
E478749
|
entity |
| Predicate | distanceFromPuertoRioTranquilo |
P137824
|
FINISHED |
| Object | short boat ride |
—
|
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: short boat ride | Statement: [Cuevas de Mármol, distanceFromPuertoRioTranquilo, short boat ride]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPuertoRioTranquilo Context triple: [Cuevas de Mármol, distanceFromPuertoRioTranquilo, short boat ride]
-
A.
distanceFromSantoDomingo
Indicates the spatial distance between a given entity and the location of Santo Domingo.
-
B.
distanceToPraia
Indicates the measured distance between an entity and the location Praia.
-
C.
distanceFromPorto
Indicates the measured distance between a given place or entity and the city of Porto.
-
D.
distanceToRioDeJaneiroCity
Indicates the physical distance between a given entity’s location and the city of Rio de Janeiro.
-
E.
distanceToHavana
Indicates the measured spatial distance between a given entity’s location and the city of Havana.
- F. None of above. chosen
Provenance (4 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c49d408190b3a42bada3675133 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.