Triple
T18037587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ELC |
E431551
|
entity |
| Predicate | subsequentLettersIndicate |
P129539
|
FINISHED |
| Object | county or city within voivodeship |
—
|
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: county or city within voivodeship | Statement: [ELC, subsequentLettersIndicate, county or city within voivodeship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subsequentLettersIndicate Context triple: [ELC, subsequentLettersIndicate, county or city within voivodeship]
-
A.
followsLetter
Indicates that one element in a sequence comes immediately after another element in alphabetical or ordered letter arrangement.
-
B.
secondLetterRepresents
Indicates that the second letter of one entity stands for, symbolizes, or denotes another entity or concept.
-
C.
letterSequence
Indicates that one sequence of letters directly follows or is ordered in relation to another within a larger string or alphabetic arrangement.
-
D.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
E.
subsequentOrder
Indicates that one order occurs after or follows another order in sequence.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3bc3208190a6db569e79f06232 |
completed | April 19, 2026, 11:36 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:25 a.m.