Triple
T10267930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tagum |
E240757
|
entity |
| Predicate | distanceFromDavaoCity |
P93027
|
FINISHED |
| Object | approximately 55 kilometers |
—
|
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 55 kilometers | Statement: [Tagum, distanceFromDavaoCity, approximately 55 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDavaoCity Context triple: [Tagum, distanceFromDavaoCity, approximately 55 kilometers]
-
A.
distanceFromManila
Indicates the measured spatial distance between a given entity’s location and the city of Manila.
-
B.
approxDistanceFromCebuCity
Indicates that one entity is located at an approximate distance from Cebu City.
-
C.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
-
D.
distanceToDaNang_km
Indicates the distance, measured in kilometers, between a given location and Da Nang.
-
E.
distanceFromNaha
Indicates the spatial distance between a given location and Naha.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d285812c8190ab910dc85c53eebf |
completed | April 7, 2026, 9:46 a.m. |
Created at: April 6, 2026, 11:34 a.m.