Triple
T2596209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chogolisa |
E58235
|
entity |
| Predicate | rankingByHeightInWorld |
P2472
|
FINISHED |
| Object | 36 |
—
|
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: 36 | Statement: [Chogolisa, rankingByHeightInWorld, 36]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingByHeightInWorld Context triple: [Chogolisa, rankingByHeightInWorld, 36]
-
A.
rankByHeightWorld
chosen
Indicates an ordering of entities based on their relative height compared to all others in the world.
-
B.
rankAmongTallestBuildings
Indicates that one building is among the tallest buildings within a specified group, area, or category.
-
C.
rankInCityByHeight
Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
-
D.
rankByLengthInWorld
Indicates ordering entities within a given world or context based on their length, from shortest to longest or vice versa.
-
E.
titleHolderRank
Indicates the relative position or level of precedence assigned to a title holder within a ranked order or hierarchy.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd42b3cd4819093b2cab78de1f66c |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.