Triple
T11962083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Santiago Metro) |
E284691
|
entity |
| Predicate | servesCommune |
P42362
|
FINISHED |
| Object | Macul |
E292545
|
NE FINISHED |
How this triple was built (2 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: Macul | Statement: [Line 4 (Santiago Metro), servesCommune, Macul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macul Context triple: [Line 4 (Santiago Metro), servesCommune, Macul]
-
A.
Macul
chosen
Macul is a commune in Santiago, Chile, known as a primarily residential and educational area that also hosts major sports venues.
-
B.
Malaun
Malaun is a historic hill town and former fortress area in Himachal Pradesh, India, known for its strategic role in early 19th-century Anglo-Gurkha conflicts.
-
C.
Marcali
Marcali is a small town in southwestern Hungary known for its agricultural surroundings and role as a local administrative and service center in Somogy County.
-
D.
Melaque
Melaque is a coastal town in Jalisco, Mexico, known for its relaxed beach atmosphere, tourism, and role as a popular vacation spot on the Pacific coast.
-
E.
Maala
Maala is a town located within Bouira Province in northern Algeria.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69f4592fa9a48190a0450e3d0c57c4d3 |
completed | May 1, 2026, 7:41 a.m. |
Created at: April 8, 2026, 9:45 p.m.