Triple
T151338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman-Kosh |
E3437
|
entity |
| Predicate | featureType |
P5048
|
FINISHED |
| Object | summit |
—
|
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: summit | Statement: [Roman-Kosh, featureType, summit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureType Context triple: [Roman-Kosh, featureType, summit]
-
A.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
B.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
C.
hasUrbanFeature
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
D.
serviceAreaCharacteristic
Indicates a relationship where a service area is associated with a specific attribute or feature that characterizes it.
-
E.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580f55a88190b37b54ee0ed5ac7c |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565adaf48190b68ae4444ff83ccd |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256ea776081908fec36c3fdfb8d84 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.