Triple
T22257160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friendly Fires |
E550122
|
entity |
| Predicate | hasSong |
P20452
|
FINISHED |
| Object |
Paris
"Paris" is an indie dance track by British band Friendly Fires, known for its shimmering synths, upbeat rhythm, and evocative lyrics about escape and longing.
|
E1530304
|
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: Paris | Statement: [Friendly Fires, hasSong, Paris]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris Context triple: [Friendly Fires, hasSong, Paris]
-
A.
Paris
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
-
B.
Paris
Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
-
C.
Paris
Paris is an American hip hop artist and producer known for his politically charged, socially conscious lyrics and militant themes.
-
D.
Paris
Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
-
E.
Paris
Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
- 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: Paris Triple: [Friendly Fires, hasSong, Paris]
Generated description
"Paris" is an indie dance track by British band Friendly Fires, known for its shimmering synths, upbeat rhythm, and evocative lyrics about escape and longing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paris Target entity description: "Paris" is an indie dance track by British band Friendly Fires, known for its shimmering synths, upbeat rhythm, and evocative lyrics about escape and longing.
-
A.
Paris
"Paris" is a hit electronic-pop single by The Chainsmokers, known for its nostalgic lyrics and mellow, atmospheric production.
-
B.
Paris
"Paris" is a 2017 electronic dance music single by The Chainsmokers that became a major international hit.
-
C.
Paris
Paris is an American hip hop artist and producer known for his politically charged, socially conscious lyrics and militant themes.
-
D.
Paris
Paris is a 1928 Broadway musical comedy with music and lyrics by Cole Porter that helped establish his reputation as a leading American songwriter.
-
E.
Paris
Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c3cf64819087e270a1f50e629e |
completed | April 28, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0acc86e96c8190abd165311cd3a334 |
completed | May 18, 2026, 8:23 a.m. |
| NEDg | Description generation | batch_6a0acfbe5b1881909b6fb940a7dac7e5 |
completed | May 18, 2026, 8:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ad10980388190a2694295a19f726d |
completed | May 18, 2026, 8:42 a.m. |
Created at: April 16, 2026, 8:39 p.m.