Triple
T4858389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 8 (Mexico City Metro) |
E108592
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Aculco
Aculco is a Mexico City Metro station located in the eastern part of the city, serving local commuters on Line 8.
|
E476265
|
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: Aculco | Statement: [Line 8 (Mexico City Metro), hasStation, Aculco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aculco Context triple: [Line 8 (Mexico City Metro), hasStation, Aculco]
-
A.
Apodaca
Apodaca is a rapidly growing industrial city and suburb of Monterrey in the Mexican state of Nuevo León.
-
B.
Tecali
Tecali is a Mexican town renowned for its traditional crafts, particularly the production of Talavera pottery and stonework.
-
C.
San Miguel
San Miguel is a town located within Bolívar Province in central Ecuador, known for its Andean setting and local agricultural activities.
-
D.
San Miguel
San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
-
E.
San Miguel
San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
- 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: Aculco Triple: [Line 8 (Mexico City Metro), hasStation, Aculco]
Generated description
Aculco is a Mexico City Metro station located in the eastern part of the city, serving local commuters on Line 8.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aculco Target entity description: Aculco is a Mexico City Metro station located in the eastern part of the city, serving local commuters on Line 8.
-
A.
Apodaca
Apodaca is a rapidly growing industrial city and suburb of Monterrey in the Mexican state of Nuevo León.
-
B.
Tecali
Tecali is a Mexican town renowned for its traditional crafts, particularly the production of Talavera pottery and stonework.
-
C.
San Miguel
San Miguel is a town located within Bolívar Province in central Ecuador, known for its Andean setting and local agricultural activities.
-
D.
San Miguel
San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
-
E.
San Miguel
San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5b2f008190a5fd11d3aec165fb |
completed | March 20, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67dd3df4819092a59dfb85d10683 |
completed | March 21, 2026, 9:41 a.m. |
| NEDg | Description generation | batch_69be695f90e88190912cac612ea680f2 |
completed | March 21, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be69b578708190951ebc93ecbaee7d |
completed | March 21, 2026, 9:49 a.m. |
Created at: March 20, 2026, 1:26 p.m.