Triple
T12280019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Socotra Airport |
E292692
|
entity |
| Predicate | distanceFromHadibu |
P103994
|
FINISHED |
| Object | approximately 12 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 12 kilometers | Statement: [Socotra Airport, distanceFromHadibu, approximately 12 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromHadibu Context triple: [Socotra Airport, distanceFromHadibu, approximately 12 kilometers]
-
A.
distanceFromMhamid
Indicates the spatial distance between an entity and the reference location Mhamid.
-
B.
distanceToHeilbronn
Indicates the spatial distance between a given entity or location and the city of Heilbronn.
-
C.
distancedFrom
Indicates that one entity is physically or metaphorically kept at a certain distance or separation from another entity.
-
D.
distanceFromHanaTown (miles)
Indicates the number of miles separating a given place or entity from Hana Town.
-
E.
distanceToBawtry
Indicates the spatial distance between a given entity and the location of Bawtry.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d9261b7f088190b69fe6961015fce3 |
completed | April 10, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:52 p.m.