Triple
T15932364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luxembourgish franc |
E386352
|
entity |
| Predicate | hadDistinctCoins |
P121036
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Luxembourgish franc, hadDistinctCoins, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadDistinctCoins Context triple: [Luxembourgish franc, hadDistinctCoins, true]
-
A.
hasCoins
Indicates that an entity possesses or holds one or more coins.
-
B.
coinageFeature
Indicates a characteristic, design element, or attribute that is present on or associated with a particular coin or type of coinage.
-
C.
coinedDenomination
Indicates that an entity created or introduced a particular name, term, or denomination for something.
-
D.
hasDistinctNumeralsFrom
Indicates that two numeral representations are composed of different digit symbols, sharing no numerals in common.
-
E.
coinsCollectedFor
Indicates that a certain number of coins has been gathered or accumulated in order to benefit or be used for a particular entity or purpose.
- F. None of above. chosen
Provenance (4 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_69d86da750008190987eb26be3f6c118 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d37cd88190ab50760f1783e20c |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e17d48cc9c8190b03fd07ae2e9dfd8 |
completed | April 17, 2026, 12:22 a.m. |
Created at: April 10, 2026, 4:52 a.m.