Triple
T2160007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Line 3 |
E47977
|
entity |
| Predicate | notableStation |
P3858
|
FINISHED |
| Object |
Zapata
Zapata is a Mexico City Metro station on Line 3, named after revolutionary leader Emiliano Zapata and known for its cultural displays and transfer connection to Line 12.
|
E240235
|
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: Zapata | Statement: [Metro Line 3, notableStation, Zapata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zapata Context triple: [Metro Line 3, notableStation, Zapata]
-
A.
Madero
Madero is a coastal city in the Mexican state of Tamaulipas, known for its oil industry and the popular Miramar Beach on the Gulf of Mexico.
-
B.
Hidalgo
Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
-
C.
Garza
Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
-
D.
Navojoa
Navojoa is a city in the southern part of the state of Sonora, Mexico, known as an agricultural and commercial center in the Mayo River valley.
-
E.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
- 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: Zapata Triple: [Metro Line 3, notableStation, Zapata]
Generated description
Zapata is a Mexico City Metro station on Line 3, named after revolutionary leader Emiliano Zapata and known for its cultural displays and transfer connection to Line 12.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zapata Target entity description: Zapata is a Mexico City Metro station on Line 3, named after revolutionary leader Emiliano Zapata and known for its cultural displays and transfer connection to Line 12.
-
A.
Madero
Madero is a coastal city in the Mexican state of Tamaulipas, known for its oil industry and the popular Miramar Beach on the Gulf of Mexico.
-
B.
Hidalgo
Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
-
C.
Garza
Garza is a Spanish-language surname of Basque origin that is common in Mexico and among people of Hispanic heritage.
-
D.
Navojoa
Navojoa is a city in the southern part of the state of Sonora, Mexico, known as an agricultural and commercial center in the Mayo River valley.
-
E.
Esquivel
Esquivel is a Spanish-language surname borne by various notable figures in literature, politics, and the arts across Latin America.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8894d481908eda9363fd36fea6 |
completed | March 7, 2026, 5:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58e9ceb08190871ff9c57ece23c0 |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae5a3db428819083d73b4295c4e829 |
completed | March 9, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a9b72188190bceb31975461206f |
completed | March 9, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:45 p.m.