Triple
T21258743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gaochang Ruins |
E523938
|
entity |
| Predicate | distanceFromTurpan |
P143416
|
FINISHED |
| Object | about 30 km southeast of Turpan city center |
—
|
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 30 km southeast of Turpan city center | Statement: [Gaochang Ruins, distanceFromTurpan, about 30 km southeast of Turpan city center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTurpan Context triple: [Gaochang Ruins, distanceFromTurpan, about 30 km southeast of Turpan city center]
-
A.
distanceFromSamarkand_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Samarkand.
-
B.
distanceFromAlmaty_km
Indicates the distance, measured in kilometers, between a given place or object and the city of Almaty.
-
C.
distanceToKyzylorda
Indicates the spatial distance between a given entity or location and the city of Kyzylorda.
-
D.
distanceToKhiva
Indicates the spatial distance between a given location or object and the city of Khiva.
-
E.
distanceFromBeijing_km
Indicates the physical distance, measured in kilometers, between a given place or object and Beijing.
- 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_69e0b5156d7881909bd4f83676590715 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735e477d08190be17ad5384d69a80 |
completed | April 21, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
| PDg | Predicate description generation | batch_69e5f9943ed881909ef49045c5bcf6df |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 16, 2026, 3:59 p.m.