Triple
T18153263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menzel Bourguiba |
E434560
|
entity |
| Predicate | distanceToBizerte |
P130654
|
FINISHED |
| Object | about 20 km southwest |
—
|
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: about 20 km southwest | Statement: [Menzel Bourguiba, distanceToBizerte, about 20 km southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBizerte Context triple: [Menzel Bourguiba, distanceToBizerte, about 20 km southwest]
-
A.
distanceToTunis
Indicates the spatial distance between a given entity’s location and the city of Tunis.
-
B.
distanceToMisrata_km
Indicates the physical distance, measured in kilometers, between a given location and Misrata.
-
C.
distanceFromBeirut
Indicates the measured spatial distance between a given entity’s location and the city of Beirut.
-
D.
distanceFromSanaa
Indicates the spatial distance between an entity and the location of Sanaa.
-
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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de39a8f481908d1752767d0aae0e |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:30 a.m.