Triple
T7783294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harriet Pitt |
E187176
|
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.
Harriet
Harriet is a biographical drama film about the life and heroism of abolitionist Harriet Tubman.
-
C.
Harriet
Harriet is the tunnel boring machine that excavated the PortMiami Tunnel beneath Biscayne Bay in Miami, Florida.
-
D.
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.
-
E.
The Underground Railroad
The Underground Railroad was a hip-hop production collective known for crafting gritty, sample-heavy beats for early 1990s West Coast rap artists.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cadf1f9c648190ac2b06d0d54035ea |
completed | March 30, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5e400d881909d6cdeb7eaac3a59 |
completed | March 30, 2026, 10:15 p.m. |
Created at: March 30, 2026, 4:22 p.m.