Triple
T7234454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poppy Montgomery |
E155186
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Poppy
Poppy is a feminine given name commonly associated with the bright red flower and often used in English-speaking countries.
|
E650027
|
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: Poppy | Statement: [Poppy Montgomery, givenName, Poppy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poppy Context triple: [Poppy Montgomery, givenName, Poppy]
-
A.
Poppy
Poppy is a glamorous love interest in the 1932 gangster film "Scarface," entangled in the dangerous world of crime and ambition surrounding the main character.
-
B.
Poppy
Poppy is the upbeat, pink-haired Troll princess who serves as the optimistic and determined protagonist of the animated film "Trolls."
-
C.
Poppy Papava
Poppy Papava is a fictional character appearing in the James Bond continuation novel "Devil May Care" by Sebastian Faulks.
-
D.
Snowdrop
Snowdrop is a Mersey Ferry passenger vessel that operates on the River Mersey, carrying commuters and tourists between Liverpool and the Wirral.
-
E.
Bloom
Bloom is a common English and Jewish surname borne by numerous notable figures in literature, academia, and the arts.
- 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: Poppy Triple: [Poppy Montgomery, givenName, Poppy]
Generated description
Poppy is a feminine given name commonly associated with the bright red flower and often used in English-speaking countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Poppy Target entity description: Poppy is a feminine given name commonly associated with the bright red flower and often used in English-speaking countries.
-
A.
Poppy
Poppy is a glamorous love interest in the 1932 gangster film "Scarface," entangled in the dangerous world of crime and ambition surrounding the main character.
-
B.
Poppy
Poppy is the upbeat, pink-haired Troll princess who serves as the optimistic and determined protagonist of the animated film "Trolls."
-
C.
Poppy Papava
Poppy Papava is a fictional character appearing in the James Bond continuation novel "Devil May Care" by Sebastian Faulks.
-
D.
Snowdrop
Snowdrop is a Mersey Ferry passenger vessel that operates on the River Mersey, carrying commuters and tourists between Liverpool and the Wirral.
-
E.
Bloom
Bloom is a common English and Jewish surname borne by numerous notable figures in literature, academia, and the arts.
- 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_69c688143bfc81908d4176617735e601 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea130e5c819087f74883760fe327 |
completed | March 27, 2026, 8:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cc2d96588190bcf150cbfe4d015c |
completed | March 28, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_69c7cce6a290819096ff68333cd3a3cf |
completed | March 28, 2026, 12:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7cd9966e481909eb3c23bb59777d9 |
completed | March 28, 2026, 12:46 p.m. |
Created at: March 27, 2026, 2:55 p.m.