Triple
T12652918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mora, Missouri |
E302208
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Mora (given name or surname) |
E269846
|
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: Mora (given name or surname) | Statement: [Mora, Missouri, namedAfter, Mora (given name or surname)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mora (given name or surname) Context triple: [Mora, Missouri, namedAfter, Mora (given name or surname)]
-
A.
Mora
Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
-
B.
Mora
Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
-
C.
Mora
chosen
Mora is a surname of Hungarian origin most notably borne by the German-Hungarian writer Terézia Mora.
-
D.
Mora
Mora is a canton in Costa Rica’s San José Province known for its rural landscapes, agricultural activities, and small-town communities.
-
E.
Namin
Namin is a city in Iran known for its location in the mountainous, historically rich Ardabil region in the northwest of the country.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96160730c81909e1aa3efb51bf159 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688104d48190939933b93b7e60cc |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:18 p.m.