Triple
T19139993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinners Like Me |
E468530
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Lightning
"Lightning" is a country song by Eric Church from his debut album "Sinners Like Me," noted for its somber narrative and reflective lyrics.
|
E1359962
|
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: Lightning | Statement: [Sinners Like Me, hasTrack, Lightning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lightning Context triple: [Sinners Like Me, hasTrack, Lightning]
-
A.
Lightning
"Lightning" is a bestselling suspense novel by Dean Koontz that blends thriller, science fiction, and supernatural elements in a time-bending story of fate and protection.
-
B.
Lightning
Lightning is the athletic mascot representing Sage Hill School’s sports teams and school spirit.
-
C.
Lightning
Lightning is the blue winged horse mascot that represents the Middle Tennessee State University Blue Raiders athletic teams.
-
D.
Lightning
Lightning is the nickname of the Milton Keynes Lightning, a professional ice hockey team based in Milton Keynes, England.
-
E.
Lightning
The Lightning was a British supersonic fighter aircraft renowned for its exceptional climb rate and speed, serving as a key interceptor for the Royal Air Force during the Cold War.
- 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: Lightning Triple: [Sinners Like Me, hasTrack, Lightning]
Generated description
"Lightning" is a country song by Eric Church from his debut album "Sinners Like Me," noted for its somber narrative and reflective lyrics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lightning Target entity description: "Lightning" is a country song by Eric Church from his debut album "Sinners Like Me," noted for its somber narrative and reflective lyrics.
-
A.
Lightning
"Lightning" is a bestselling suspense novel by Dean Koontz that blends thriller, science fiction, and supernatural elements in a time-bending story of fate and protection.
-
B.
Lightning
Lightning is the nickname of the Milton Keynes Lightning, a professional ice hockey team based in Milton Keynes, England.
-
C.
Lightning
Lightning is Apple’s proprietary compact connector used for charging and data transfer on many of its mobile devices and accessories.
-
D.
Lightning
Lightning is the athletic mascot representing Sage Hill School’s sports teams and school spirit.
-
E.
Lightning
The Lightning was a British supersonic fighter aircraft renowned for its exceptional climb rate and speed, serving as a key interceptor for the Royal Air Force during the Cold War.
- 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_69d8dd0796a48190b34ce4cd9d3f3be5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3f094f88190996279d7b548edea |
completed | April 20, 2026, 8:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05e685266c81909f6c3053d6e50849 |
completed | May 14, 2026, 3:13 p.m. |
| NEDg | Description generation | batch_6a05e9db3fac8190b484ed5e9ff1e961 |
completed | May 14, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05ea546230819087e952db04137591 |
completed | May 14, 2026, 3:29 p.m. |
Created at: April 10, 2026, 12:05 p.m.