Triple
T3355604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanwood |
E70596
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Griffith |
E25800
|
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: Griffith | Statement: [Hanwood, nearbyCity, Griffith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Griffith Context triple: [Hanwood, nearbyCity, Griffith]
-
A.
Griffith
chosen
Griffith is a major regional city in New South Wales, Australia, known for its agricultural production, especially wine and citrus, and its culturally diverse community.
-
B.
Redfield
Redfield is a surname of English origin borne by various notable individuals across fields such as politics, science, and the arts.
-
C.
Blackwood
Blackwood is a town in south Wales known for its coal-mining heritage and location in the Sirhowy Valley.
-
D.
Farguson
Farguson is an alternative spelling of the surname Ferguson, which is of Scottish origin.
-
E.
Líster
Líster is a Spanish surname most notably associated with Enrique Líster, a prominent communist military commander during the Spanish Civil War.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2419a808190a54fc03eeec6e42d |
completed | March 8, 2026, 5:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3253b03e8819082a5bf5bd5c5d5cb |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:13 p.m.