Triple
T15899318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siege of the Alcázar |
E385542
|
entity |
| Predicate | commander |
P1061
|
FINISHED |
| Object | José Moscardó |
E1082965
|
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: José Moscardó | Statement: [Siege of the Alcázar, commander, José Moscardó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: José Moscardó Context triple: [Siege of the Alcázar, commander, José Moscardó]
-
A.
José Moscardó
chosen
José Moscardó was a Spanish Nationalist general best known for leading the staunch defense of the Toledo Alcázar during the early stages of the Spanish Civil War.
-
B.
José Marco
José Marco is a Spanish politician who served as President of the autonomous community of Aragon.
-
C.
José Solchaga
José Solchaga was a Spanish Nationalist military officer who played a significant command role during the Spanish Civil War.
-
D.
Francisco Boira
Francisco Boira is a Spanish actor best known for his role in Pedro Almodóvar’s acclaimed film "Bad Education."
-
E.
José Luis Alexanco
José Luis Alexanco was a Spanish visual artist known for his innovative work in experimental and computer-generated art, as well as his involvement in avant-garde cultural movements in Spain.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007d9849a08190a575f19e816e6df2 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 4:51 a.m.