Triple
T9293369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tristana |
E223574
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Lola Gaos
Lola Gaos was a Spanish film, theater, and television actress known for her intense character roles in mid-20th-century Spanish cinema.
|
E789837
|
NE FINISHED |
How this triple was built (4 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: Lola Gaos | Statement: [Tristana, castMember, Lola Gaos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lola Gaos Context triple: [Tristana, castMember, Lola Gaos]
-
A.
Lola Flores
Lola Flores was a celebrated Spanish flamenco singer, dancer, and actress, iconic in 20th-century Spanish popular culture.
-
B.
Lola Valente
Lola Valente is a fictional character best known as the ambitious and talented protagonist of the Mexican teen telenovela "Lola, érase una vez."
-
C.
Lola Salazar
Lola Salazar is a fictional character appearing in the narrative of *The Wolf Song*.
-
D.
Lolita Pulido
Lolita Pulido is the spirited young Californio noblewoman who serves as Don Diego Vega’s love interest in Johnston McCulley’s Zorro stories, notably in "The Mark of Zorro."
-
E.
Mina Clavero
Mina Clavero is a popular riverside tourist town in central Argentina known for its natural beaches, clear rivers, and surrounding Sierras de Córdoba mountain scenery.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lola Gaos Triple: [Tristana, castMember, Lola Gaos]
Generated description
Lola Gaos was a Spanish film, theater, and television actress known for her intense character roles in mid-20th-century Spanish cinema.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lola Gaos Target entity description: Lola Gaos was a Spanish film, theater, and television actress known for her intense character roles in mid-20th-century Spanish cinema.
-
A.
Lola Flores
Lola Flores was a celebrated Spanish flamenco singer, dancer, and actress, iconic in 20th-century Spanish popular culture.
-
B.
Lola Valente
Lola Valente is a fictional character best known as the ambitious and talented protagonist of the Mexican teen telenovela "Lola, érase una vez."
-
C.
Lola Salazar
Lola Salazar is a fictional character appearing in the narrative of *The Wolf Song*.
-
D.
Lolita Pulido
Lolita Pulido is the spirited young Californio noblewoman who serves as Don Diego Vega’s love interest in Johnston McCulley’s Zorro stories, notably in "The Mark of Zorro."
-
E.
Mina Clavero
Mina Clavero is a popular riverside tourist town in central Argentina known for its natural beaches, clear rivers, and surrounding Sierras de Córdoba mountain scenery.
- F. None of above. chosen
Provenance (5 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0898b3288190a627a58bfd9c57fe |
completed | April 1, 2026, 11:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b241251c81909aa4e8bcf5cd9c2e |
completed | April 4, 2026, 6:40 a.m. |
| NEDg | Description generation | batch_69d0b3324e7c8190b928928bbfbdbadf |
completed | April 4, 2026, 6:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0b3d40da08190b25118a0901728da |
completed | April 4, 2026, 6:46 a.m. |
Created at: March 30, 2026, 7:35 p.m.