Triple
T14347561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lochinvar National Park |
E355765
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Monze |
E885889
|
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: Monze | Statement: [Lochinvar National Park, nearestCity, Monze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monze Context triple: [Lochinvar National Park, nearestCity, Monze]
-
A.
Monze
chosen
Monze is a town in southern Zambia known as an important agricultural and trading center, particularly for maize and cattle.
-
B.
Rinas
Rinas is a village near Tirana in Albania best known as the location of the country’s main international airport.
-
C.
Opata
Opata refers to an Indigenous people and their now largely extinct Uto-Aztecan language historically spoken in northern Mexico, particularly in the present-day state of Sonora.
-
D.
Mado
Mado is a French film written by Gérard Brach, known as one of his notable screenwriting works.
-
E.
Ifo
Ifo is a town in Ogun State, southwestern Nigeria, known as a historically significant Awori settlement and an important local commercial center.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8e8b81bc8190ace2a575faf55cc0 |
completed | April 14, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46a12ad08190a2f0dc5890ed5ce9 |
completed | May 8, 2026, 2:12 a.m. |
Created at: April 10, 2026, 1:14 a.m.