Triple
T563493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salt March |
E13503
|
entity |
| Predicate | distanceTraveled |
P16230
|
FINISHED |
| Object | about 390 kilometers |
—
|
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 390 kilometers | Statement: [Salt March, distanceTraveled, about 390 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceTraveled Context triple: [Salt March, distanceTraveled, about 390 kilometers]
-
A.
distance
Indicates the spatial separation or length between two points, objects, or locations.
-
B.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
C.
peakRouteMileage
Indicates the maximum total distance covered by a particular route over a specified period or under peak operating conditions.
-
D.
distanceFromTerminus
Indicates the measured distance of an entity from a defined endpoint or terminus along a route, path, or sequence.
-
E.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a712bc48190ba298b3c76ab11cc |
completed | March 1, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69a494c044648190a98589ab18935216 |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498ff0c0081908947376a38b10d72 |
completed | March 1, 2026, 7:52 p.m. |
Created at: March 1, 2026, 7:32 p.m.