Triple
T17031109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haymitch Abernathy |
E413194
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Suzanne Collins |
E459302
|
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: Suzanne Collins | Statement: [Haymitch Abernathy, createdBy, Suzanne Collins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suzanne Collins Context triple: [Haymitch Abernathy, createdBy, Suzanne Collins]
-
A.
Suzanne Collins
chosen
Suzanne Collins is an American author best known for writing the bestselling dystopian young adult series "The Hunger Games."
-
B.
Lois Lowry
Lois Lowry is an American author best known for her award-winning young adult novels such as "The Giver" and "Number the Stars."
-
C.
Veronica Roth
Veronica Roth is an American novelist best known for writing the bestselling young adult dystopian Divergent series.
-
D.
James Dashner
James Dashner is an American author best known for writing the young adult dystopian science fiction series "The Maze Runner."
-
E.
CR Snow
CR Snow is a leading Chinese brewing company best known for producing Snow Beer, one of the world’s top-selling beer brands.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d9e7d481909d3d5bd241bd68f1 |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b5748bc8190832737a70219e7a1 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.