Triple
T14155144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beresfield |
E350795
|
entity |
| Predicate | nearbySuburb |
P41355
|
FINISHED |
| Object | Tarro |
E350794
|
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: Tarro | Statement: [Beresfield, nearbySuburb, Tarro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarro Context triple: [Beresfield, nearbySuburb, Tarro]
-
A.
Tarro
chosen
Tarro is a suburban railway station in the Hunter Region of New South Wales, Australia, serving the local community on the Main Northern line.
-
B.
Barugo
Barugo is a coastal municipality in the province of Leyte in the Eastern Visayas region of the Philippines, known for its agricultural economy and rural communities.
-
C.
Antuco
Antuco is a stratovolcano in the Chilean Andes known for its symmetrical cone and location within the Southern Volcanic Zone.
-
D.
Harroz
Harroz is the surname of Joseph Harroz Jr., an American academic administrator and president of the University of Oklahoma.
-
E.
Tabasalu
Tabasalu is a small town in northern Estonia that serves as the main local hub for the surrounding Harku Parish near the capital, Tallinn.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6135744c81909a43d659f5fe2895 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ec6448819087e50aac964ec637 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 12:58 a.m.