Triple
T7854038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hualpén |
E182125
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object | Talcahuano |
E74676
|
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: Talcahuano | Statement: [Hualpén, hasTransportConnection, Talcahuano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talcahuano Context triple: [Hualpén, hasTransportConnection, Talcahuano]
-
A.
Talcahuano
chosen
Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
-
B.
Maipú
Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
-
C.
Maipú
Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
-
D.
Rancagua
Rancagua is a major Chilean city known for its mining industry and historical significance in the country’s independence, serving as an important commercial and administrative center south of Santiago.
-
E.
Talca
Talca is a major city in central Chile known as an administrative, commercial, and agricultural hub in the Maule Valley.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb1a72cfdc8190a3186c4c2894f571 |
completed | March 31, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec5f00b48190b35f7cab67e7e5f9 |
completed | April 1, 2026, 9:58 a.m. |
Created at: March 30, 2026, 4:51 p.m.