Triple
T24945949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woiwurrung language |
E624184
|
entity |
| Predicate | hasExamplePlaceName |
P158147
|
FINISHED |
| Object | Merri |
—
|
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: Merri | Statement: [Woiwurrung language, hasExamplePlaceName, Merri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExamplePlaceName Context triple: [Woiwurrung language, hasExamplePlaceName, Merri]
-
A.
hasExamplePlaceName
chosen
Indicates that an entity is associated with a specific place name used as an example.
-
B.
hasPlaceNamesIn
Indicates that something contains, references, or is associated with one or more place names within it.
-
C.
hasExampleSurname
Indicates that an entity is associated with a sample or illustrative surname used as an example rather than a real or primary family name.
-
D.
hasPlaceNamesakeIn
Indicates that something is named after a particular place or location.
-
E.
exampleOfToponymicName
Indicates that a name is a toponymic name derived from or based on a place or geographic location.
- 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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 5:54 a.m.