Triple
T6000251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Increase Carpenter |
E133574
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Increase |
E24822
|
NE 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: Increase | Statement: [Increase Carpenter, givenName, Increase]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Increase Context triple: [Increase Carpenter, givenName, Increase]
-
A.
Increase
chosen
Increase is a rare given name most famously borne by Increase Mather, a prominent 17th-century New England Puritan minister and political figure.
-
B.
Gain
Gain is a popular Procter & Gamble laundry detergent brand known for its strong, long-lasting fragrances.
-
C.
Growing
"Growing" is an autobiographical work by Leonard Woolf recounting his years as a colonial administrator in Ceylon and his political and personal development during that period.
-
D.
Growing
"Growing" is an episode of the BBC nature documentary series *The Private Life of Plants* that explores how plants develop and increase in size over time.
-
E.
Up
Up is a critically acclaimed 2009 Pixar animated film that follows an elderly widower and a young boy on a fantastical balloon-lifted house adventure, noted for its emotional depth and imaginative storytelling.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c00870ddbc81909880fa3864f4f38d |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee5e7bc8190aaa87605fa7b102e |
completed | March 22, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1136338088190be26e6393b04e018 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:05 p.m.