Triple
T6673134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Batopilas |
E151781
|
entity |
| Predicate | roadAccessFrom |
P22549
|
FINISHED |
| Object | Creel |
E153514
|
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: Creel | Statement: [Batopilas, roadAccessFrom, Creel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Creel Context triple: [Batopilas, roadAccessFrom, Creel]
-
A.
Creel
chosen
Creel is a small mountain town in Mexico’s Sierra Tarahumara that serves as a popular gateway for tourists exploring the Copper Canyon region.
-
B.
River Deer
The River Deer is a small river in Devon, England, that forms part of the local drainage system before joining the River Tamar.
-
C.
Snow Creek
Snow Creek is a small ski and snowboard resort known for its winter sports facilities and family-friendly atmosphere.
-
D.
Pike
Pike is an English surname of Old English origin, often associated with people who lived near a pointed hill or carried a pike as a weapon.
-
E.
Kason
Kason is the second month of the traditional Burmese calendar, associated with religious observances such as the Buddha’s birth, enlightenment, and death anniversaries.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b0cb78b08190923685712cbba5d8 |
completed | March 27, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7a10ec08190983a66b874a1d541 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:03 p.m.