Triple
T16051027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longcheng |
E389351
|
entity |
| Predicate | nearFeatureType |
P5048
|
FINISHED |
| Object | river valley |
—
|
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: river valley | Statement: [Longcheng, nearFeatureType, river valley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearFeatureType Context triple: [Longcheng, nearFeatureType, river valley]
-
A.
nearbyFeature
Indicates that one entity is located close to or in the immediate vicinity of another entity.
-
B.
nearestPointTo
Indicates the point that is closest in distance to a given reference point or object among a set of candidates.
-
C.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
D.
featureType
chosen
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
E.
nearestArea
Indicates that one area is the closest in distance to a given reference point or region compared to all other candidate areas.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.