Triple
T17497100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrolterra |
E426091
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Neda |
—
|
NE NERFINISHED |
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: Neda | Statement: [Ferrolterra, hasMunicipality, Neda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neda Context triple: [Ferrolterra, hasMunicipality, Neda]
-
A.
Neda
chosen
Neda is a coastal municipality in the province of A Coruña, Galicia, Spain, situated along the Ferrol estuary.
-
B.
Neda Armian
Neda Armian is a film producer best known for her work on acclaimed independent films such as "Rachel Getting Married."
-
C.
Emanuela
Emanuela is a feminine given name, commonly used in various European and Latin cultures, that is a variant of Emmanuelle and ultimately derived from the Hebrew name Emmanuel.
-
D.
Hadiya
Hadiya is a Cushitic ethnic group primarily living in southern Ethiopia, known for their distinct language and cultural traditions.
-
E.
Laleh
Laleh is an Iranian-Swedish singer-songwriter, producer, and former actress known for her eclectic pop music and introspective lyrics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520f6790819092c36e0e4ecc4cd3 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.