Triple
T20253109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hagnaya Port |
E498609
|
entity |
| Predicate | distanceFromDescription |
P17802
|
FINISHED |
| Object | several hours by land from Cebu City |
—
|
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: several hours by land from Cebu City | Statement: [Hagnaya Port, distanceFromDescription, several hours by land from Cebu City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDescription Context triple: [Hagnaya Port, distanceFromDescription, several hours by land from Cebu City]
-
A.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
B.
distanceCharacteristic
chosen
Indicates a relationship where an entity is described or constrained by some property or measure of distance (e.g., range, spacing, or separation).
-
C.
distancesFrom
Indicates the measured spatial separation between one entity and one or more other entities.
-
D.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
E.
distanceProvidedBy
Indicates that a specific distance value is supplied or made available by a particular source or provider.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673a986e08190b1ff2992ed5f8772 |
completed | April 20, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:41 p.m.