Triple
T14393175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHI |
E356893
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | alt.chi |
E356895
|
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: alt.chi | Statement: [CHI, hasTrack, alt.chi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: alt.chi Context triple: [CHI, hasTrack, alt.chi]
-
A.
CHI
CHI is the Amtrak station code for Chicago Union Station, the primary intercity rail hub in Chicago, Illinois.
-
B.
CHI
CHI is the official FIFA country code used to represent the Chile national football team in international competitions and records.
-
C.
CHI
CHI is the standard sports abbreviation used to represent Chicago-based teams, in this case referring to the Chicago Hounds.
-
D.
CHI
CHI is the premier international conference in human-computer interaction, showcasing cutting-edge research on how people interact with digital technologies.
-
E.
CHI Conference
chosen
The CHI Conference is a premier annual international academic conference focused on human–computer interaction and human factors in computing systems.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de902b9acc8190817ffa848a76a880 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551b006c8190b84449f2e2b59b62 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.