Triple
T31342477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zouar |
E799343
|
entity |
| Predicate | distanceToLibyaBorder |
P203655
|
FINISHED |
| Object | relatively close |
—
|
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: relatively close | Statement: [Zouar, distanceToLibyaBorder, relatively close]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLibyaBorder Context triple: [Zouar, distanceToLibyaBorder, relatively close]
-
A.
directionFromLibya
Indicates the relative compass direction of one place or object as measured outward starting from Libya.
-
B.
distanceToEgyptianBorder
Indicates the measured distance between a given location and the border of Egypt.
-
C.
distanceToTunisia
Indicates the measured or calculated distance between a given entity’s location and the country of Tunisia.
-
D.
distanceToMisrata_km
Indicates the physical distance, measured in kilometers, between a given location and Misrata.
-
E.
distanceToTripoli_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Tripoli.
- 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01beacf8a88190ac643a75c7a0efc4 |
completed | May 11, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_6a01be152c8c8190bb19d64a683e2aae |
completed | May 11, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_6a01beac1334819082be0e4cf017e00c |
completed | May 11, 2026, 11:34 a.m. |
Created at: April 29, 2026, 9:17 p.m.