Triple
T13223774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umag |
E314821
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Umago |
E314821
|
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: Umago | Statement: [Umag, alternativeName, Umago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umago Context triple: [Umag, alternativeName, Umago]
-
A.
Umag
chosen
Umag is a coastal town in northwestern Croatia known for its tourism, historic old town, and annual ATP tennis tournament.
-
B.
Lagunna
Lagunna is a titled chief within the Oyo Mesi, the council of kingmakers and principal nobles in the traditional Oyo Yoruba political system.
-
C.
Lagoona
Lagoona is a creative work or character whose style and themes are shaped by the fantastical, fairy-filled world and motifs associated with Oberon from literature and mythology.
-
D.
Looma
Looma is an alternative name for Loma, which may refer to various places, peoples, or entities sharing that designation.
-
E.
Omoku
Omoku is a prominent town in Nigeria’s oil-rich Niger Delta region, serving as an important commercial and administrative hub in Rivers State.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf74d708190a61d8ad938653b06 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3407388190bef886884cb75912 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:19 p.m.