Triple
T14412065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abracadabra |
E357353
|
entity |
| Predicate | director |
P255
|
FINISHED |
| Object | Pablo Berger |
E357356
|
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: Pablo Berger | Statement: [Abracadabra, director, Pablo Berger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pablo Berger Context triple: [Abracadabra, director, Pablo Berger]
-
A.
Pablo Berger
chosen
Pablo Berger is a Spanish film director and screenwriter best known internationally for his acclaimed silent black-and-white film "Blancanieves."
-
B.
Carlos Pibernat
Carlos Pibernat was an architect known for designing the headquarters of Banco de la Nación Argentina, a prominent financial institution in the country.
-
C.
Pablo G. del Amo
Pablo G. del Amo was a Spanish film editor known for his work on notable films of the country's New Wave cinema.
-
D.
Alejandro Brodersohn
Alejandro Brodersohn is a film editor known for his work on the romantic drama "The Lake House."
-
E.
Luis Zahera
Luis Zahera is a Spanish actor known for his intense character roles in film and television, for which he has earned critical acclaim and major national awards.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d8137348190b332e27f3d71d4f0 |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 10, 2026, 1:17 a.m.