Triple
T3906570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kate Morton |
E87215
|
entity |
| Predicate | publicationYearOfDebut |
P45532
|
FINISHED |
| Object | 2006 |
—
|
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: 2006 | Statement: [Kate Morton, publicationYearOfDebut, 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicationYearOfDebut Context triple: [Kate Morton, publicationYearOfDebut, 2006]
-
A.
debutYear
Indicates the year in which an entity first appeared, was introduced, or made its initial public debut.
-
B.
debutWorkReleaseYear
chosen
Indicates the calendar year in which an entity’s first published or publicly released work originally came out.
-
C.
firstSeriesYear
Indicates the year in which a series (such as a TV show, book series, or sports league season) first began or was initially released.
-
D.
firstRunningYear
Indicates the year in which something (such as an event, service, or operation) first began running or was initially active.
-
E.
productionStartYear
Indicates the year in which the production of an item, work, or entity first began.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.