Triple
T12502622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laporte |
E298866
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Laporte |
E894266
|
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: Laporte | Statement: [Laporte, hasVariant, Laporte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laporte Context triple: [Laporte, hasVariant, Laporte]
-
A.
Laporte
chosen
Laporte is a small borough that serves as the county seat of Sullivan County in northeastern Pennsylvania.
-
B.
Laporte
Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
-
C.
Naper
Naper is a surname most notably associated with Joseph Naper, an early American pioneer and founder of Naperville, Illinois.
-
D.
Portage
Portage is Gentoo Linux’s highly configurable source-based package management system that automates compiling, installing, and updating software.
-
E.
de Kalb
De Kalb is a German-born French military officer who served as a major general in the Continental Army during the American Revolutionary War and became a symbol of foreign support for the American cause.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfcea188190a929db1aabe1a286 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb38e048190bbc96244b71953b6 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.