Triple
T10862151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Hay |
E256431
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hay |
E11959
|
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: Hay | Statement: [Susan Hay, familyName, Hay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hay Context triple: [Susan Hay, familyName, Hay]
-
A.
Hay
chosen
Hay is a rural service town in the Riverina region of southwestern New South Wales, Australia, known for its agricultural production and historic role as a transport and wool-growing center.
-
B.
Haynt
Haynt was a Yiddish-language newspaper that served as an important platform for Jewish journalism and literature in early 20th-century Eastern Europe.
-
C.
Ham
Ham is a suburban riverside district in southwest London, England, known for its historic houses, green spaces, and proximity to the River Thames.
-
D.
Ham
Ham is a biblical figure known as one of Noah’s sons and a progenitor of several ancient peoples mentioned in the Hebrew Bible.
-
E.
Ham
Ham is a small town in the Somme department of northern France, known historically for its medieval fortress and strategic location.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7515238108190a72eb8cd147f223d |
completed | April 9, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7d350748190821a4413c1eb7106 |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:20 p.m.