Triple
T22503348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CAP |
E556329
|
entity |
| Predicate | tradingVenueMIC |
P6939
|
FINISHED |
| Object | XPAR |
—
|
NE NERFINISHED |
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: XPAR | Statement: [CAP, tradingVenueMIC, XPAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XPAR Context triple: [CAP, tradingVenueMIC, XPAR]
-
A.
XPAR
chosen
XPAR is the Market Identifier Code (MIC) for Euronext Paris, the primary stock exchange in France.
-
B.
CXP
CXP is the FAA location identifier for Carson City Airport in Carson City, Nevada.
-
C.
CXP
CXP is a high-density optical transceiver module form factor designed for short-reach, multi-lane high-speed data communications such as 100 Gigabit Ethernet.
-
D.
Xtime
Xtime is a Cox Automotive company that provides software solutions to help automotive dealerships manage service scheduling, customer communications, and retention.
-
E.
Xilinx
Xilinx is a leading semiconductor company best known for its programmable logic devices, particularly FPGAs and related development tools.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5a01888190ba65a05616b63cbe |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.