Triple
T2789059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Laporte |
E61881
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Laporte
Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
|
E298866
|
NE FINISHED |
How this triple was built (4 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: [Otto Laporte, familyName, Laporte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laporte Context triple: [Otto Laporte, familyName, Laporte]
-
A.
Portage
Portage is Gentoo Linux’s highly configurable source-based package management system that automates compiling, installing, and updating software.
-
B.
Saint‑Cloud
Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
-
C.
Eastland
Eastland is a surname most notably associated with James Eastland, a long-serving and influential U.S. senator from Mississippi.
-
D.
Berger Junction
Berger Junction is a major road intersection and commercial transport hub in the Wuse district of Abuja, Nigeria.
-
E.
Supaul
Supaul is a town in the Indian state of Bihar known primarily as an administrative and commercial center for the surrounding region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Laporte Triple: [Otto Laporte, familyName, Laporte]
Generated description
Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laporte Target entity description: Laporte is a surname of French origin borne by various notable individuals across fields such as science, sports, and politics.
-
A.
Portage
Portage is Gentoo Linux’s highly configurable source-based package management system that automates compiling, installing, and updating software.
-
B.
Saint‑Cloud
Saint-Cloud is a western suburb of Paris, France, historically notable for its royal château and as the site of key political events during the French Revolution and Napoleonic era.
-
C.
Eastland
Eastland is a surname most notably associated with James Eastland, a long-serving and influential U.S. senator from Mississippi.
-
D.
Berger Junction
Berger Junction is a major road intersection and commercial transport hub in the Wuse district of Abuja, Nigeria.
-
E.
Supaul
Supaul is a town in the Indian state of Bihar known primarily as an administrative and commercial center for the surrounding region.
- F. None of above. chosen
Provenance (5 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddb3d63c8190b3ab5fa363c69db8 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6589558819088442f09db328dac |
completed | March 10, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69afc6d485d88190b281abec460ff24d |
completed | March 10, 2026, 7:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afc750fee08190bf3c112f6f204af4 |
completed | March 10, 2026, 7:25 a.m. |
Created at: March 6, 2026, 9:58 p.m.