Triple
T22343905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corpus Inscriptionum Latinarum |
E552342
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | CIL |
—
|
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: CIL | Statement: [Corpus Inscriptionum Latinarum, abbreviation, CIL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CIL Context triple: [Corpus Inscriptionum Latinarum, abbreviation, CIL]
-
A.
CIL
chosen
CIL is the standard scholarly abbreviation for the Corpus Inscriptionum Latinarum, the comprehensive collection of ancient Latin inscriptions.
-
B.
CIL
CIL is the abbreviation for the Committee on Import Licensing, a World Trade Organization body that oversees and reviews members’ import licensing procedures to ensure they are transparent and consistent with WTO rules.
-
C.
CIL
CIL is the low-level, platform-independent bytecode language used by the .NET framework to represent compiled programs before just-in-time compilation.
-
D.
CIL
CIL is the reporting mark used to identify the Monon Railroad, a historic Midwestern U.S. railroad line.
-
E.
CIL I
CIL I is the first volume of the Corpus Inscriptionum Latinarum, containing a foundational collection of early Latin inscriptions.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15796b2288190b10e9402abf35fd3 |
completed | April 29, 2026, 12:57 a.m. |
Created at: April 16, 2026, 8:43 p.m.