Triple
T34666639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TKPN |
E890274
|
entity |
| Predicate | secondLetterSubregion |
P199093
|
FINISHED |
| Object | K |
—
|
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: K | Statement: [TKPN, secondLetterSubregion, K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondLetterSubregion Context triple: [TKPN, secondLetterSubregion, K]
-
A.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
B.
originSubregion
Indicates the specific subregional area from which an entity originates or is derived.
-
C.
subregionName
Indicates that one region is identified by a specific name used for a smaller or subordinate geographic or administrative area within a larger region.
-
D.
regionSub
Indicates that one region is a subregion or contained part of another, larger region.
-
E.
secondaryLanguageRegion
Indicates a region where a language is used in a secondary or supporting role rather than as the primary language.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1e3e13c08190bb8990c44716b746 |
completed | May 9, 2026, 11:45 a.m. |
| PD | Predicate disambiguation | batch_69ff1dfcaf2c8190aaf2b428d57b7782 |
completed | May 9, 2026, 11:43 a.m. |
| PDg | Predicate description generation | batch_69ff1e3d5f488190ba6e4f024128fb99 |
completed | May 9, 2026, 11:45 a.m. |
Created at: May 1, 2026, 2:05 a.m.