Triple
T11408957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teodor |
E270314
|
entity |
| Predicate | isCognateWith |
P2527
|
FINISHED |
| Object | Teodoro |
E270315
|
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: Teodoro | Statement: [Teodor, isCognateWith, Teodoro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teodoro Context triple: [Teodor, isCognateWith, Teodoro]
-
A.
Teodoro
chosen
Teodoro is a given name, commonly used in Romance-language countries, that corresponds to the English name Theodore.
-
B.
Filiberto
Filiberto was a Puerto Rican nationalist and militant leader associated with the Puerto Rican independence movement.
-
C.
Mariano
Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
-
D.
Quirino
Quirino is a landlocked province in the Cagayan Valley region of the Philippines known for its mountainous terrain, caves, and eco-tourism attractions.
-
E.
Marcos
Marcos is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, that derives from the Latin name Marcus.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014e72748190a01bde2f0105cedb |
completed | April 9, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5b845ed488190b7680ddf09177ea0 |
completed | April 20, 2026, 5:23 a.m. |
Created at: April 8, 2026, 9:34 p.m.