Triple
T28638139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyclone |
E724846
|
entity |
| Predicate | firstMainDCUAppearanceYear |
P78407
|
FINISHED |
| Object | 2007 |
—
|
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: 2007 | Statement: [Cyclone, firstMainDCUAppearanceYear, 2007]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMainDCUAppearanceYear Context triple: [Cyclone, firstMainDCUAppearanceYear, 2007]
-
A.
firstShowYear
Indicates the year in which something (such as a show, event, or work) was first presented or made publicly available.
-
B.
firstPrototypeYear
Indicates the year in which the first prototype of an entity was created or completed.
-
C.
firstPublicationYearOfAppearance
chosen
Indicates the year in which an entity (such as a work or character) first appeared in a published form.
-
D.
firstMajorUseYear
Indicates the calendar year in which something was first put into major or primary use.
-
E.
firstArrivalYear
Indicates the calendar year in which an entity first arrived at or was initially present in a specified place or context.
- F. None of above.
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_69f01d8328c48190bc0e5f9b9b848582 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: April 28, 2026, 4:42 a.m.