Triple
T26744200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trench of Death |
E674347
|
entity |
| Predicate | distanceFromYserTower |
P197840
|
FINISHED |
| Object | approximately 1 km |
—
|
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 1 km | Statement: [Trench of Death, distanceFromYserTower, approximately 1 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromYserTower Context triple: [Trench of Death, distanceFromYserTower, approximately 1 km]
-
A.
distanceToHoverla
Indicates the measured distance between a given entity’s location and Hoverla.
-
B.
distanceToFez
Indicates the spatial distance between a given entity and the location identified as Fez.
-
C.
distanceFromBabylon
Indicates the spatial distance between a given location or object and the city of Babylon.
-
D.
distanceFromChora
Indicates the spatial distance between an entity and the place referred to as Chora.
-
E.
distanceToTheEntrance
Indicates the spatial distance between a given entity and the entrance of a specified place or structure.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69feb342994081909481ec8ec5d44928 |
completed | May 9, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69feb046e4e48190b96649aa28529cc9 |
completed | May 9, 2026, 3:55 a.m. |
| PDg | Predicate description generation | batch_69feb3419158819082f4666077535ca9 |
completed | May 9, 2026, 4:08 a.m. |
Created at: April 27, 2026, 3:50 a.m.