Triple
T17185343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Excellent Italian Greyhound |
E417091
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Genuine Lulabelle
Genuine Lulabelle is a racing Italian Greyhound known for competing on the track.
|
E1256323
|
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: Genuine Lulabelle | Statement: [Excellent Italian Greyhound, hasTrack, Genuine Lulabelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Genuine Lulabelle Context triple: [Excellent Italian Greyhound, hasTrack, Genuine Lulabelle]
-
A.
Laa-Laa
Laa-Laa is the yellow, fun-loving Teletubby known for her cheerful personality and love of playing with her orange ball.
-
B.
Loulou
Loulou is a given name or nickname commonly used in various cultures, often as a diminutive form of names like Louise or Louis.
-
C.
Sheba, Baby
Sheba, Baby is a 1975 blaxploitation crime-action film starring Pam Grier as a tough private investigator returning to her hometown to battle corrupt businessmen threatening her father's business.
-
D.
Lulu Ferocity
Lulu Ferocity is a central character known for her bold, dynamic presence and fierce, fashion-forward persona in the narrative of "Pose."
-
E.
The Lenny
The Lenny is a track featured in the Balf Quarry racing environment, known for its challenging layout and integration into the quarry-themed course.
- 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: Genuine Lulabelle Triple: [Excellent Italian Greyhound, hasTrack, Genuine Lulabelle]
Generated description
Genuine Lulabelle is a racing Italian Greyhound known for competing on the track.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Genuine Lulabelle Target entity description: Genuine Lulabelle is a racing Italian Greyhound known for competing on the track.
-
A.
Laa-Laa
Laa-Laa is the yellow, fun-loving Teletubby known for her cheerful personality and love of playing with her orange ball.
-
B.
Loulou
Loulou is a given name or nickname commonly used in various cultures, often as a diminutive form of names like Louise or Louis.
-
C.
Sheba, Baby
Sheba, Baby is a 1975 blaxploitation crime-action film starring Pam Grier as a tough private investigator returning to her hometown to battle corrupt businessmen threatening her father's business.
-
D.
Lulu Ferocity
Lulu Ferocity is a central character known for her bold, dynamic presence and fierce, fashion-forward persona in the narrative of "Pose."
-
E.
The Lenny
The Lenny is a track featured in the Balf Quarry racing environment, known for its challenging layout and integration into the quarry-themed course.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42d9556c881908ccaee4ef77dbe1f |
completed | April 19, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a015fcc424081908a7e74df0523443e |
completed | May 11, 2026, 4:49 a.m. |
| NEDg | Description generation | batch_6a016184e0c0819099320b32bc471cad |
completed | May 11, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0162692420819097b99a71ec470861 |
completed | May 11, 2026, 5 a.m. |
Created at: April 10, 2026, 5:37 a.m.