Triple
T1573145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludovica |
E33585
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object |
Ludo
Ludo is a common short form or nickname for the given name Ludovica.
|
E179533
|
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: Ludo | Statement: [Ludovica, shortForm, Ludo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ludo Context triple: [Ludovica, shortForm, Ludo]
-
A.
Trichinopoly
Trichinopoly, now commonly known as Tiruchirappalli, is a historic city in Tamil Nadu, India, renowned for its ancient temples and strategic location on the banks of the Kaveri River.
-
B.
Pengo
Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
-
C.
The Gamester
The Gamester is a Caroline-era tragicomedy play by English dramatist James Shirley, centered on themes of gambling, honor, and social intrigue.
-
D.
Solitaire
Solitaire is a fictional psychic tarot reader and Bond girl who appears as a key ally and love interest to James Bond in the novel and film "Live and Let Die."
-
E.
Marbles
Marbles is a deadly children's-game-based round in the series "Squid Game" where players wager their lives over a simple game of chance and strategy.
- 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: Ludo Triple: [Ludovica, shortForm, Ludo]
Generated description
Ludo is a common short form or nickname for the given name Ludovica.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ludo Target entity description: Ludo is a common short form or nickname for the given name Ludovica.
-
A.
Trichinopoly
Trichinopoly, now commonly known as Tiruchirappalli, is a historic city in Tamil Nadu, India, renowned for its ancient temples and strategic location on the banks of the Kaveri River.
-
B.
Pengo
Pengo is a Dravidian language spoken primarily by the Pengo people in parts of central India, especially in Odisha and neighboring regions.
-
C.
The Gamester
The Gamester is a Caroline-era tragicomedy play by English dramatist James Shirley, centered on themes of gambling, honor, and social intrigue.
-
D.
Solitaire
Solitaire is a fictional psychic tarot reader and Bond girl who appears as a key ally and love interest to James Bond in the novel and film "Live and Let Die."
-
E.
Marbles
Marbles is a deadly children's-game-based round in the series "Squid Game" where players wager their lives over a simple game of chance and strategy.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908bb9c648190933fd19bcc1cb9a4 |
completed | March 5, 2026, 4:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4028bc5881909dbe847229dd63bb |
completed | March 8, 2026, 9:23 a.m. |
| NEDg | Description generation | batch_69ad41930d208190b34531e3f35fa58b |
completed | March 8, 2026, 9:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad422752348190b42ebc3781a6e8a5 |
completed | March 8, 2026, 9:32 a.m. |
Created at: March 4, 2026, 7:27 p.m.