Triple
T31565943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khmeric languages |
E805412
|
entity |
| Predicate | dominantLanguageCommunity |
P5562
|
FINISHED |
| Object | Khmer people |
—
|
NE NERFINISHED |
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: Khmer people | Statement: [Khmeric languages, dominantLanguageCommunity, Khmer people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dominantLanguageCommunity Context triple: [Khmeric languages, dominantLanguageCommunity, Khmer people]
-
A.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
B.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
C.
languageFamilyDominant
Indicates that one language family holds a primary or prevailing status over others within a given context (such as a region, population, or system).
-
D.
dominantTraditionalLanguage
Indicates that one language is the primary or most widely used traditional language within a given context or community.
-
E.
dominantLocalLanguage
Indicates that one language is the primary or most widely used language within a specific local area or community.
- 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_69f348d2ee94819091918d1789398c29 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
Created at: April 30, 2026, 10:17 p.m.