Triple
T9091801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago Province |
E217904
|
entity |
| Predicate | contains |
P35
|
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: [Santiago Province, contains, Macul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macul Context triple: [Santiago Province, contains, 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.
Maala
Maala is a town located within Bouira Province in northern Algeria.
-
C.
Marau
Marau is an Oceanic language spoken by a small community in Papua New Guinea.
-
D.
Makus
Makus is an alternative form of the name Maccus, a historical given name of Norse and Gaelic origin.
-
E.
Makatsch
Makatsch is the surname of German actress and television presenter Heike Makatsch, known for her roles in films such as "Love Actually" and "Resident Evil."
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b18b24819097b525ddad3a85c0 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d017ecc8b4819094dc0b009484ec00 |
completed | April 3, 2026, 7:41 p.m. |
Created at: March 30, 2026, 7:14 p.m.