Triple
T1642905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Pitt |
E35512
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Harriet |
E8574
|
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: Harriet | Statement: [Harriet Pitt, givenName, Harriet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harriet Context triple: [Harriet Pitt, givenName, Harriet]
-
A.
Harriet
chosen
Harriet is the given name of Harriet Beecher Stowe, the 19th-century American author best known for writing the anti-slavery novel "Uncle Tom's Cabin."
-
B.
Uncle Tom's Cabin
Uncle Tom's Cabin is an 1852 anti-slavery novel that powerfully influenced public opinion in the United States and abroad in the years leading up to the American Civil War.
-
C.
Shirley
Shirley is a small town in north-central Massachusetts served by commuter rail on the MBTA Fitchburg Line.
-
D.
Shirley
Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
-
E.
Shirley
Shirley is an English surname of Old English origin that has also become a common given name.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90a3f4d8c8190aa0a44d1c9b1a7f0 |
completed | March 5, 2026, 4:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad60a0096c81909dc723d0db95481e |
completed | March 8, 2026, 11:42 a.m. |
Created at: March 4, 2026, 7:28 p.m.