Triple
T402673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Madre del Sur |
E9318
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Guerrero
Guerrero is a coastal state in southwestern Mexico known for its mountainous terrain, including part of the Sierra Madre del Sur, and popular tourist destinations such as Acapulco.
|
E50767
|
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: Guerrero | Statement: [Sierra Madre del Sur, locatedIn, Guerrero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guerrero Context triple: [Sierra Madre del Sur, locatedIn, Guerrero]
-
A.
Hidalgo
Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
-
B.
Navarro
Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
-
C.
Jaruco
Jaruco is a municipality in western Cuba known for its historic town and the nearby Jaruco Escalante hills and parklands.
-
D.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
E.
Diego
Diego is a given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
- 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: Guerrero Triple: [Sierra Madre del Sur, locatedIn, Guerrero]
Generated description
Guerrero is a coastal state in southwestern Mexico known for its mountainous terrain, including part of the Sierra Madre del Sur, and popular tourist destinations such as Acapulco.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guerrero Target entity description: Guerrero is a coastal state in southwestern Mexico known for its mountainous terrain, including part of the Sierra Madre del Sur, and popular tourist destinations such as Acapulco.
-
A.
Hidalgo
Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
-
B.
Navarro
Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
-
C.
Jaruco
Jaruco is a municipality in western Cuba known for its historic town and the nearby Jaruco Escalante hills and parklands.
-
D.
Cáqueza
Cáqueza is a small municipality and town in the Andean region of central Colombia, known for its rural landscapes and proximity to Bogotá in the department of Cundinamarca.
-
E.
Diego
Diego is a given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
- 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2eca0e2048190a7bf360257965e56 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a41042136c819096dde34d5608feec |
completed | March 1, 2026, 10:09 a.m. |
| NEDg | Description generation | batch_69a410a87f4c8190916688197abc1f16 |
completed | March 1, 2026, 10:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a410ff91e08190959720b0315a7989 |
completed | March 1, 2026, 10:12 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.