Triple
T4370669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carrick |
E98887
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Kyle
Kyle is a town in South Ayrshire, Scotland, historically associated with the former district of Carrick.
|
E436246
|
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: Kyle | Statement: [Carrick, borders, Kyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyle Context triple: [Carrick, borders, Kyle]
-
A.
Kyle
Kyle is a musical artist known for being a featured performer on the song "Surf."
-
B.
Kevin
Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
-
C.
Kevin
Kevin is the young boy protagonist of the 1981 fantasy adventure film "Time Bandits," who joins a group of time-traveling dwarfs on a series of historical escapades.
-
D.
Ken
Ken is the iconic male doll character and Barbie’s counterpart, portrayed in the 2023 film as a comically self-aware and insecure figure exploring identity and patriarchy.
-
E.
Ken
Ken is the nickname of Ken Dryden, the legendary Canadian Hall of Fame goaltender best known for backstopping the Montreal Canadiens to multiple Stanley Cup championships in the 1970s.
- 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: Kyle Triple: [Carrick, borders, Kyle]
Generated description
Kyle is a town in South Ayrshire, Scotland, historically associated with the former district of Carrick.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kyle Target entity description: Kyle is a town in South Ayrshire, Scotland, historically associated with the former district of Carrick.
-
A.
Kyle
Kyle is a musical artist known for being a featured performer on the song "Surf."
-
B.
Kevin
Kevin is the given name of Kevin Garnett, a Hall of Fame American professional basketball player known for his intensity, versatility, and NBA championship with the Boston Celtics.
-
C.
Kevin
Kevin is the young boy protagonist of the 1981 fantasy adventure film "Time Bandits," who joins a group of time-traveling dwarfs on a series of historical escapades.
-
D.
Ken
Ken is the iconic male doll character and Barbie’s counterpart, portrayed in the 2023 film as a comically self-aware and insecure figure exploring identity and patriarchy.
-
E.
Ken
Ken is the nickname of Ken Dryden, the legendary Canadian Hall of Fame goaltender best known for backstopping the Montreal Canadiens to multiple Stanley Cup championships in the 1970s.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3521cb7ec8190b7b79675871d97d8 |
completed | March 12, 2026, 11:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e50bcc9481909b0b9d60198dce63 |
completed | March 14, 2026, 10:45 p.m. |
| NEDg | Description generation | batch_69b5eeadd68881909820a75aaff9d8d5 |
completed | March 14, 2026, 11:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5ef36f2bc8190a21e0f2fadbdd697 |
completed | March 14, 2026, 11:28 p.m. |
Created at: March 12, 2026, 11:17 p.m.