Triple
T14887522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summit High School |
E359666
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Summit |
E1098378
|
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: Summit | Statement: [Summit High School, city, Summit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Summit Context triple: [Summit High School, city, Summit]
-
A.
Summit
"Summit" is a track from the album *China* by electronic music composer Vangelis, known for its atmospheric, synthesizer-driven soundscapes.
-
B.
Summit
Summit is a high-end luxury trim level of the Jeep Grand Cherokee, featuring premium materials, advanced technology, and upscale comfort and styling.
-
C.
Summit
chosen
Summit is a Metra commuter rail station in Summit, Illinois, serving passengers on the Heritage Corridor line between Chicago and Joliet.
-
D.
Summit
Summit is a high-performance supercomputer at Oak Ridge National Laboratory that was once the world’s fastest, designed for large-scale scientific and artificial intelligence research.
-
E.
Snow Summit
Snow Summit is a popular Southern California ski and snowboard resort located in the Big Bear Lake area of the San Bernardino Mountains.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5f22c08190a9530cbd78cfc801 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 2:08 a.m.