Triple
T14637621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chop Shop |
E343646
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Alejandro |
E39964
|
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: Alejandro | Statement: [Chop Shop, mainCharacter, Alejandro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alejandro Context triple: [Chop Shop, mainCharacter, Alejandro]
-
A.
Alejandro
chosen
Alejandro is the Spanish form of the given name Alexander, commonly used in Spanish-speaking countries.
-
B.
Alejandro
"Alejandro" is a pop song produced by RedOne, best known as one of Lady Gaga’s hit singles from her album "The Fame Monster."
-
C.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
D.
Vicente
Vicente is a given name, common in Spanish- and Portuguese-speaking countries, that corresponds to the English name Vincent.
-
E.
Julio
Julio is a central character in the Spanish mystery drama series "High Seas," which follows intrigue and secrets aboard a luxury transatlantic ocean liner in the 1940s.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4aca6448190adf1042dfbfef716 |
completed | April 14, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda934ec3c81909eb3c3a54260436b |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:26 a.m.