Triple
T7997257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Marqués |
E186157
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Pedro Escobedo
Pedro Escobedo is a municipality in the state of Querétaro, Mexico, known for its agricultural activities and growing industrial development.
|
E763827
|
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: Pedro Escobedo | Statement: [El Marqués, borders, Pedro Escobedo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pedro Escobedo Context triple: [El Marqués, borders, Pedro Escobedo]
-
A.
Alfredo Escalera
Alfredo Escalera is a former Puerto Rican professional boxer best known as a long-reigning WBC super featherweight champion during the 1970s.
-
B.
Horacio Gutiérrez
Horacio Gutiérrez is a Cuban-American classical pianist renowned for his virtuosic technique and interpretations of the Romantic repertoire.
-
C.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
D.
Raúl Dávalos
Raúl Dávalos is an editor known for his work on the film "Cronos."
-
E.
José Chávez
José Chávez is a Spanish-speaking personal name shared by multiple individuals, most commonly associated with Latin American figures in sports, politics, and the arts.
- 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: Pedro Escobedo Triple: [El Marqués, borders, Pedro Escobedo]
Generated description
Pedro Escobedo is a municipality in the state of Querétaro, Mexico, known for its agricultural activities and growing industrial development.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pedro Escobedo Target entity description: Pedro Escobedo is a municipality in the state of Querétaro, Mexico, known for its agricultural activities and growing industrial development.
-
A.
Alfredo Escalera
Alfredo Escalera is a former Puerto Rican professional boxer best known as a long-reigning WBC super featherweight champion during the 1970s.
-
B.
Horacio Gutiérrez
Horacio Gutiérrez is a Cuban-American classical pianist renowned for his virtuosic technique and interpretations of the Romantic repertoire.
-
C.
Sergio Avelar
Sergio Avelar is an actor known for his role in the inspirational sports drama film "McFarland, USA."
-
D.
Raúl Dávalos
Raúl Dávalos is an editor known for his work on the film "Cronos."
-
E.
José Chávez
José Chávez is a Spanish-speaking personal name shared by multiple individuals, most commonly associated with Latin American figures in sports, politics, and the arts.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c98e39081908904d36a31bd6768 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfaae99194819095cf9b74267956a4 |
completed | April 3, 2026, 11:56 a.m. |
| NEDg | Description generation | batch_69cfac76d0f8819090c2bff520db52f4 |
completed | April 3, 2026, 12:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfad04e514819084bf30b8f026c031 |
completed | April 3, 2026, 12:05 p.m. |
Created at: March 30, 2026, 5:17 p.m.