Triple
T11962254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Línea 6 |
E284696
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Lo Valledor
Lo Valledor is a metro station on Santiago, Chile’s underground network, serving the city’s Line 6 corridor.
|
E956942
|
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: Lo Valledor | Statement: [Línea 6, hasStation, Lo Valledor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lo Valledor Context triple: [Línea 6, hasStation, Lo Valledor]
-
A.
Valle de Bujaruelo
Valle de Bujaruelo is a scenic Pyrenean valley in northern Spain known for its rugged mountain landscapes, hiking routes, and proximity to the French border.
-
B.
Valle de Tena
Valle de Tena is a scenic Pyrenean valley in northeastern Spain known for its mountain landscapes, ski resorts, and outdoor recreation.
-
C.
Soto de Viñuelas
Soto de Viñuelas is a protected natural area in the Madrid region of Spain, known for its Mediterranean woodlands, wildlife, and role as a peri-urban green space near the Jarama River.
-
D.
Cuarte de Huerva
Cuarte de Huerva is a municipality in northeastern Spain, situated near the city of Zaragoza in the autonomous community of Aragon.
-
E.
Noguera Pallaresa
Noguera Pallaresa is a river in the Catalan Pyrenees of northeastern Spain, renowned for its whitewater rafting and kayaking.
- 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: Lo Valledor Triple: [Línea 6, hasStation, Lo Valledor]
Generated description
Lo Valledor is a metro station on Santiago, Chile’s underground network, serving the city’s Line 6 corridor.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lo Valledor Target entity description: Lo Valledor is a metro station on Santiago, Chile’s underground network, serving the city’s Line 6 corridor.
-
A.
Valle de Bujaruelo
Valle de Bujaruelo is a scenic Pyrenean valley in northern Spain known for its rugged mountain landscapes, hiking routes, and proximity to the French border.
-
B.
Valle de Tena
Valle de Tena is a scenic Pyrenean valley in northeastern Spain known for its mountain landscapes, ski resorts, and outdoor recreation.
-
C.
Soto de Viñuelas
Soto de Viñuelas is a protected natural area in the Madrid region of Spain, known for its Mediterranean woodlands, wildlife, and role as a peri-urban green space near the Jarama River.
-
D.
Cuarte de Huerva
Cuarte de Huerva is a municipality in northeastern Spain, situated near the city of Zaragoza in the autonomous community of Aragon.
-
E.
Noguera Pallaresa
Noguera Pallaresa is a river in the Catalan Pyrenees of northeastern Spain, renowned for its whitewater rafting and kayaking.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037848f481908276716675464464 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4594054f08190b28b35f62dfb9198 |
completed | May 1, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69f45f89d5b08190a87312d96e61898a |
completed | May 1, 2026, 8:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f464a5191881908e291943996169cb |
completed | May 1, 2026, 8:30 a.m. |
Created at: April 8, 2026, 9:45 p.m.