Triple
T6369826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paloma Faith |
E143318
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Paloma |
E200070
|
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: Paloma | Statement: [Paloma Faith, givenName, Paloma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paloma Context triple: [Paloma Faith, givenName, Paloma]
-
A.
Paloma
chosen
Paloma is a feminine given name of Spanish origin meaning "dove," famously borne by designer Paloma Picasso.
-
B.
Paloma
Paloma is a popular Mexican tequila-based cocktail typically made with grapefruit soda or juice and lime, known for its refreshing, citrusy flavor.
-
C.
Blanca
Blanca is a feminine given name, common in Spanish-speaking cultures, that corresponds to the English and French name Blanche.
-
D.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
-
E.
Colombina
Colombina is a clever, flirtatious maid character from the Italian commedia dell’arte tradition, often portrayed as Harlequin’s witty and resourceful lover.
- 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_69c008d8c61081908bcaf61510d881ed |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c068277f6c81908e6a55e006f0c229 |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62d8bce3481909b0bf7533b330d1f |
completed | March 27, 2026, 7:11 a.m. |
Created at: March 22, 2026, 4:33 p.m.