Triple
T33830998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itang |
E867097
|
entity |
| Predicate | distanceFromGambelaTown |
P206690
|
FINISHED |
| Object | tens of kilometers (approximate) |
—
|
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: tens of kilometers (approximate) | Statement: [Itang, distanceFromGambelaTown, tens of kilometers (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromGambelaTown Context triple: [Itang, distanceFromGambelaTown, tens of kilometers (approximate)]
-
A.
distanceFromBahirDar
Indicates the spatial distance separating a given entity or location from Bahir Dar.
-
B.
distanceFromAddisAbaba
Indicates the physical distance between a given location and Addis Ababa.
-
C.
distanceToMekelle
Indicates the spatial distance between an entity and the city of Mekelle.
-
D.
distanceToGondar_km
Indicates the physical distance, measured in kilometers, between a given location and Gondar.
-
E.
distanceFromAsmara
Indicates the spatial distance between a given location and the city of Asmara.
- 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_69f34991dd248190a659541588506b3c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:46 a.m.