Triple
T586051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runcorn |
E15158
|
entity |
| Predicate | hasSuburb |
P747
|
FINISHED |
| Object |
Norton
Norton is a residential suburb within the town of Runcorn in Cheshire, England.
|
E73224
|
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: Norton | Statement: [Runcorn, hasSuburb, Norton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norton Context triple: [Runcorn, hasSuburb, Norton]
-
A.
Micros Systems
Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
-
B.
NCP
NCP (Network Control Protocol) was an early host-to-host communication protocol suite that enabled data exchange between computers on the ARPANET before the adoption of TCP/IP.
-
C.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
D.
Opera Software
Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
-
E.
Bolt Beranek and Newman
Bolt Beranek and Newman was a pioneering American research and engineering firm best known for its foundational role in developing the ARPANET, a precursor to the modern internet.
- 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: Norton Triple: [Runcorn, hasSuburb, Norton]
Generated description
Norton is a residential suburb within the town of Runcorn in Cheshire, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Norton Target entity description: Norton is a residential suburb within the town of Runcorn in Cheshire, England.
-
A.
Micros Systems
Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
-
B.
NCP
NCP (Network Control Protocol) was an early host-to-host communication protocol suite that enabled data exchange between computers on the ARPANET before the adoption of TCP/IP.
-
C.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
D.
Opera Software
Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
-
E.
Bolt Beranek and Newman
Bolt Beranek and Newman was a pioneering American research and engineering firm best known for its foundational role in developing the ARPANET, a precursor to the modern internet.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9a46388190a094b9ebf8dec397 |
completed | March 1, 2026, 8:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a50e25f4e4819081c8973b0f24dec0 |
completed | March 2, 2026, 4:12 a.m. |
| NEDg | Description generation | batch_69a50ea21c54819099975c66b97f97f3 |
completed | March 2, 2026, 4:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a50f2e06288190a8ddf49310ee2790 |
completed | March 2, 2026, 4:16 a.m. |
Created at: March 1, 2026, 7:33 p.m.