Triple
T11179614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SCAR |
E264502
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | SCAR |
E264502
|
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: SCAR | Statement: [SCAR, acronym, SCAR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SCAR Context triple: [SCAR, acronym, SCAR]
-
A.
SCAR
chosen
SCAR is an international scientific body that coordinates and promotes research in and about Antarctica and the Southern Ocean.
-
B.
SCAR
SCAR is the ICAO airport code for Chacalluta International Airport, which serves the city of Arica in northern Chile.
-
C.
SC4
SC4 is the commonly used abbreviation for St. Clair County Community College, a public community college located in Port Huron, Michigan.
-
D.
SCAP
SCAP was the title held by General Douglas MacArthur as the top Allied authority overseeing the occupation and reconstruction of Japan after World War II.
-
E.
SCS
SCS is Carnegie Mellon University's renowned School of Computer Science, recognized globally for pioneering research and education in computing and related fields.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e899c6288190b39e090fa9cdc883 |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4839eeaac8190826007ca126ed491 |
completed | April 19, 2026, 7:26 a.m. |
Created at: April 8, 2026, 9:29 p.m.