Triple
T15535285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherbet Land |
E370323
|
entity |
| Predicate | hasObstacles |
P52690
|
FINISHED |
| Object | sharp turns |
—
|
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: sharp turns | Statement: [Sherbet Land, hasObstacles, sharp turns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObstacles Context triple: [Sherbet Land, hasObstacles, sharp turns]
-
A.
hasObstacleType
Indicates that an entity is associated with or characterized by a specific type or category of obstacle.
-
B.
hasObjectiveHazards
Indicates that an entity is associated with concrete, externally verifiable dangers or risks.
-
C.
obstacles
chosen
Indicates that one entity presents barriers, hindrances, or impediments that block or restrict another entity’s progress, action, or interaction.
-
D.
hasNavigationHazard
Indicates that something presents or contains a condition, object, or feature that poses a risk or obstacle to safe navigation.
-
E.
obstacleHeightCharacteristic
Indicates the characteristic or measured value of an obstacle’s height in relation to a reference level or path.
- 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_69d85cc521a08190921fb50319dddc34 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e0442e327c8190b4b879c8a3cd38e3 |
completed | April 16, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69deda7a95c48190bbe29fadcf17191a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:06 a.m.