Triple
T15346304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monaro region |
E366927
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Dalgety |
E1078608
|
NE 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: Dalgety | Statement: [Monaro region, hasTown, Dalgety]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dalgety Context triple: [Monaro region, hasTown, Dalgety]
-
A.
Dalgety
chosen
Dalgety is a small rural town in New South Wales, Australia, situated on the Snowy River and known for its historic buildings and pastoral surroundings.
-
B.
McElderry
McElderry is the surname of Margaret K. McElderry, a pioneering American children's book editor and publisher.
-
C.
Cleghorn
Cleghorn is a residential neighborhood within the city of Fitchburg, Massachusetts.
-
D.
Kilgetty
Kilgetty is a small village in Pembrokeshire, Wales, known as a local residential and service hub near the coastal resort of Saundersfoot.
-
E.
Dignan
Dignan is an overly enthusiastic, idealistic small-time criminal and one of the main characters in Wes Anderson’s film "Bottle Rocket."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01f931408190828d87567cecaceb |
completed | May 9, 2026, 9:44 a.m. |
Created at: April 10, 2026, 3:17 a.m.