Triple
T30787474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chewong language |
E783992
|
entity |
| Predicate | domainOfKnowledge |
P134757
|
FINISHED |
| Object | forest ecology |
—
|
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: forest ecology | Statement: [Chewong language, domainOfKnowledge, forest ecology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: domainOfKnowledge Context triple: [Chewong language, domainOfKnowledge, forest ecology]
-
A.
knowledgeScope
chosen
Indicates the extent or range of information, topics, or understanding that an entity possesses or is concerned with.
-
B.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
-
C.
widelyStudiedIn
Indicates that something has been extensively researched, analyzed, or examined within a particular field, domain, or context.
-
D.
knowledgeType
Indicates the specific category or nature of knowledge associated with an entity or statement (e.g., factual, procedural, conceptual).
-
E.
dimensionOfStudy
Indicates the specific field, aspect, or perspective that characterizes or structures a particular study or research activity.
- 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_69f224b213c8819083886073f90b647e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6900ab06c8190856785240a8faa83 |
completed | May 3, 2026, midnight |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:41 p.m.