Triple
T22512719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Labors of Esfandiyar |
E556560
|
entity |
| Predicate | featuresObstacleType |
P67904
|
FINISHED |
| Object | desert |
—
|
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: desert | Statement: [Seven Labors of Esfandiyar, featuresObstacleType, desert]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresObstacleType Context triple: [Seven Labors of Esfandiyar, featuresObstacleType, desert]
-
A.
obstacleHeightCharacteristic
Indicates the characteristic or measured value of an obstacle’s height in relation to a reference level or path.
-
B.
hasObstacleType
chosen
Indicates that an entity is associated with or characterized by a specific type or category of obstacle.
-
C.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
D.
typicalBarrierType
Indicates the usual or characteristic type of barrier associated with or used in a given context or situation.
-
E.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
- F. None of above.
Provenance (3 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d61a27881909faed490d2b65f39 |
completed | April 29, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.