Triple
T16398107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ERC Ingolstadt |
E398235
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | ERCI |
E398233
|
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: ERCI | Statement: [ERC Ingolstadt, hasAbbreviation, ERCI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ERCI Context triple: [ERC Ingolstadt, hasAbbreviation, ERCI]
-
A.
ERCI
chosen
ERCI is the commonly used abbreviation for ERC Ingolstadt, a professional ice hockey club based in Ingolstadt, Germany.
-
B.
ERI
ERI is the Earthquake Research Institute of the University of Tokyo, a leading Japanese center for seismology and earthquake-related research.
-
C.
ERI
ERI is the former stock ticker symbol for Eldorado Resorts, a U.S.-based casino and hospitality company that later became part of Caesars Entertainment.
-
D.
ERI
ERI is the IATA airport code for Erie International Airport, a commercial airport serving Erie, Pennsylvania.
-
E.
ERI@N
ERI@N is an energy research institute at Nanyang Technological University in Singapore that focuses on sustainable energy, smart grids, and related clean technology innovations.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327cc5c9c8190ba1a70f9e430cefb |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c5bcc7c81909dc1d3a9a1b7f50a |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:09 a.m.