Triple
T28946237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temiar |
E730587
|
entity |
| Predicate | mainStatesInhabited |
P71058
|
FINISHED |
| Object | Perak |
—
|
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: Perak | Statement: [Temiar, mainStatesInhabited, Perak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainStatesInhabited Context triple: [Temiar, mainStatesInhabited, Perak]
-
A.
primaryStates
Indicates that certain states or conditions are the main or most fundamental ones within a given context or system.
-
B.
largestStateByPopulation
Indicates that the subject is the state with the highest population among a specified set of states or within a given region.
-
C.
stateMostEvidentIn
Indicates that a condition, feature, or phenomenon is most clearly or prominently manifested within a particular state or region.
-
D.
stateInhabited
chosen
Indicates that a particular state is (or was) lived in or occupied by a specified entity.
-
E.
numberOfStates
Indicates the total count of distinct states or conditions associated with an entity or system.
- 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_69f043ea0aa88190a25acbf46157995a |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 28, 2026, 8:40 a.m.